Vulnerabilities
in the EU residential
real estate sector
November 2016

Contents

Executive summary

2

Section 1 Addressing vulnerabilities in residential real estate: a key task for
macroprudential policymakers

12

1.1

The importance of residential real estate in the economy and for
macroprudential policy

12

1.2

The nature and effects of financial crises relating to residential real estate

14

1.3

Analysing vulnerabilities in residential real estate: collateral, household and
banking stretches

16

Section 2 Analysing vulnerabilities in residential real estate

21

2.1

Horizontal analysis of residential real estate vulnerabilities in EU countries

22

2.2

Vertical analysis of RRE vulnerabilities

41

Conclusions

141

List of tables and charts

143

Abbreviations

145

List of contributors

147

Annex A Overview of process and mandates

151

Annex B Methodology – Horizontal method

153

Annex C Additional key indicators for focus countries

158

Annex D Overview of assessments by third parties

161

Imprint

169

Vulnerabilities in the EU residential real estate sector November 2016
Contents

1

Executive summary
Developments in the residential real estate sector can have significant implications for
financial stability and the real economy. Residential real estate (RRE) represents a major part of
households’ wealth and constitutes a major source of collateral for lenders. Moreover, mortgages
often make up large parts of banks’ balance sheets, and are the largest and most common form of
debt among households. Furthermore, housing construction is typically an important component of
the real economy, as a source of employment, investment and growth. Experiences show that
systemic risk relating to RRE – stemming from excessive risk-taking, high leverage, misaligned
incentives and boom/bust tendencies, etc. – may lead to significant risks to domestic financial
stability and serious negative consequences for the real economy, as well as potentially leading to
negative spillovers to other countries. Vulnerabilities in RRE may manifest themselves through
direct effects – through losses of capital or funding among lenders – and indirect effects in terms of
foregone economic output, which may have second-round effects on the financial system. The
underlying sources of such vulnerabilities differ. However, they often emerge from domestic
structural features, from social and economic policies (e.g. tax deductibility of mortgage interest
payments), from cyclical developments, or combinations thereof.
Given the importance of RRE for financial and macroeconomic stability, analysing
vulnerabilities in RRE markets is a key responsibility of macroprudential authorities. Taking
a forward-looking approach and seeking to prevent the build-up of vulnerabilities is especially
1
important. Analysing vulnerabilities is also the task of the European Systemic Risk Board (ESRB),
which is mandated to conduct macroprudential oversight of the financial system within the
2
European Union (EU) in order to contribute to the prevention or mitigation of systemic risks.
With this aim, the ESRB has analysed the vulnerabilities across EU countries relating to
3
RRE. The ESRB has investigated whether there are vulnerabilities related to the RRE sector in EU
countries that may be a direct or indirect source of systemic risk to financial stability, and may also
have the potential for serious negative consequences for the real economy. The results of the
vulnerability assessment of the EU RRE sector – which represents a continuation of previous work
4
by the ESRB – are presented in this report.
The analysis of vulnerabilities is based on a comprehensive approach. First, an indicatorbased cross-country framework, developed jointly by the ESRB and the European Central Bank
(ECB), was applied to identify a set of focus countries for further analysis. Next, a country-specific
analysis of the focus countries was performed, taking account of factors relating to structural and

1

From a cost-benefit perspective, it is likely that preventing the build-up of risk is less costly than addressing vulnerabilities
that are already high.

2

Regulation (EU) No 1092/2010 of the European Parliament and of the Council of 24 November 2010 on European Union
macro-prudential oversight of the financial system and establishing a European Systemic Risk Board (OJ L 331,
15.12.2010, p.1).

3

An ESRB task force was created to undertake this analysis. The task force consists of various teams with representation
from the ESRB membership to ensure fair and consistent analysis. Participants in the task force are shown in the list of
Participants, above. See Annex A for an overview of the teams including their mandates and main forms of interaction.

4

The previous work includes that of the ESRB Expert Group on Real Estate (“Report on Residential Real Estate”, ESRB
Expert Group on Real Estate, 2015 - hereafter "ESRB 2015"), the ESRB Recommendation 2013/1 on intermediate
objectives and instruments of macro-prudential policy (2013/C 170/01) and the ESRB Handbook on
Operationalising Macro-prudential Policy in the Banking Sector (2014).

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Executive summary

2

institutional features and policy measures. Building on previous work by the ESRB, vulnerabilities
were identified and separated into three “stretches” – collateral, household and banking – where
collateral stretch captures the price levels and dynamics in RRE markets, household stretch
captures the implications of household borrowers’ debt for their consumption and other behaviour,
and banking stretch captures the potential impact of RRE developments on lenders.
The horizontal analysis revealed vulnerabilities stemming from developments in the RRE sector in
a number of EU Member States. The ESRB identified a group of eleven countries where
vulnerabilities have risen to an extent that they required further investigation from a systemic
perspective. These countries comprise: Austria, Belgium, Denmark, Estonia, Finland, Luxembourg,
Malta, the Netherlands, Slovakia, Sweden and the United Kingdom. These countries (hereafter
referred to as the “focus countries”) were subject to a second stage of in-depth, country-specific
analysis of vulnerabilities and policy measures. Overall, the findings of the country-specific analysis
were the following (also summarised in Table E.1):
•

Austria: vulnerabilities for Austria are related to the robust growth, particularly recently, in
RRE prices and mortgage credit and the risk of a further loosening in lending standards. RRE
prices in Austria have been increasing rapidly, particularly since 2011. Also, prices appear to
be above levels in line with fundamentals in Vienna, but are broadly in line with fundamentals
in the rest of Austria. More recently, the strong house price dynamics have coincided with
robust mortgage credit growth. First indications from an Oesterreichische Nationalbank
(OeNB) survey on lending standards show that standards may be weakening somewhat; in
particular, there are groups of households with new loans that have high debt-to-income (DTI)
5
and loan-to-value (LTV) ratios. Austria currently lacks borrower-based macroprudential legal
tools, although steps have been taken to make these instruments available and soft measures
(communication of expectations) have recently been used. While the policy measures that
have been taken by the Austrian authorities are appropriate given the nature of RRE
vulnerabilities in Austria, they may not be sufficient to fully address the robustly growing RRE
prices and mortgage credit, signs of weakening lending standards and groups of households
with elevated debt levels.

•

Belgium: the main RRE-related vulnerability in Belgium concerns the fast increase in overall
household indebtedness combined with groups of already highly indebted households, against
the background of a significant increase in RRE prices over the past few years. Together with
the low risk weights applied to mortgage lending by some banks, this suggests that
vulnerabilities are present in Belgium for the collateral, household and banking stretches.
Belgium has experienced robust increases in lending for house purchases and presents nonnegligible loan segments characterised by high LTV and debt service-to-income (DSTI) ratios
which are more vulnerable to adverse economic shocks. RRE prices are increasing and are
now close to their pre-crisis level, presenting signs of overvaluation compared with
fundamentals. While vulnerabilities related to the banking stretch have been addressed
through the imposition of a macroprudential risk weight add-on of 5 percentage points (p.p.)
on the domestic mortgage loan exposures of banks using the internal ratings-based (IRB)
approach, measures that explicitly address risks related to the groups of highly indebted

5

There are a number of caveats in the OeNB survey; hence the results should be interpreted with care: (1) it covers only a
relatively small market share (about 20-25% of housing loans collateralised by residential real estate); (2) its sample size
changes over time; and (3) the variance in the data between banks is quite large, also due to different methods of
calculation between banks. For this reason the results must be interpreted with care.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Executive summary

3

households have not yet been introduced. Furthermore, the trend of tightening lending
standards appears to have ended, which – given the very high credit growth – indicates that
vulnerabilities could be building up. For these reasons, the policy stance for the collateral and
household stretches is appropriate, but not expected to be sufficient.
•

Denmark: the main vulnerabilities are considered to be the rapidly rising RRE prices – in
particular in the major cities – in combination with highly indebted households. In addition, if
risks were to materialise, there may be potential spillover effects on other countries in the
Nordic-Baltic region. Households’ debt levels are very high in relation both to income and
GDP, and particularly for some households. At the same time, RRE prices are increasing,
driven by fast increases in major cities where they are approaching pre-crisis levels. Overall,
credit growth has not been very rapid, but mortgage credit institutions are increasing lending
in the major cities. Credit standards are tightening, but the high stock of household debt is not
expected to significantly decline within an appropriate time horizon given that it is not directly
addressed by the policy stance. There is a risk that the rapidly increasing RRE prices will lead
to a further increase in household indebtedness. For these reasons, the policies in place are
assessed as appropriate, but may not be sufficient to address the vulnerabilities in the
collateral and household stretches. This assessment reflects the fact that some of the
measures have only been in effect for a limited period of time and are entering into force
6
gradually, while some of them only apply to new borrowers.

•

Estonia: vulnerabilities related to residential real estate in Estonia are concentrated in the
collateral stretch. RRE prices had been rising quickly since 2009 and are close to their precrisis peak levels. However, the price growth has been driven mainly by income (which
outpaced productivity growth) rather than by credit, and RRE prices have stabilised somewhat
in the past year. Furthermore, different valuation methods suggest that, on average, RRE
prices are in line with fundamentals for the moment. Risks and vulnerabilities in the household
and banking stretches appear more contained, owing to relatively low indebtedness of the
household sector, moderate growth in RRE lending and high capital adequacy of the banking
sector. The Estonian authorities have implemented a combination of precautionary policy
measures to prevent RRE lending standards from loosening from their current level and to
increase the resilience of the banking sector. The policy measures are appropriate and
expected to be sufficient given the current level of and trend in vulnerabilities.

•

Finland: in Finland, the main vulnerabilities are considered to be the high and increasing
household indebtedness, especially among some groups of households. In addition, if risks
were to materialise, there may be potential spillover effects on other countries in the NordicBaltic region. DTI and household debt-to-GDP ratios are at their historical peaks and relatively
high by European comparison. The groups of highly indebted households are a source of
concern. The debt is concentrated in certain households: 10% of households – accounting for
almost half of the total household debt – have DTI ratios above 300%, and a significant
proportion of these have DTIs above 400%. RRE price indicators suggest that prices relative
to income and rents are close to their long-term averages; however, given the weak economic
outlook, the likelihood of a manifestation of risks in the market over the short-to-medium term

6

The LTV limit only affects new loans, while the “supervisory diamond” and the seven best practices for lending are a mix of
flow and stock measures. The change in interest deductibility will not be fully phased in before 2020 and the supervisory
diamond will not be fully implemented before 2020.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Executive summary

4

is elevated. The Finnish banking sector is highly concentrated, with large exposures to RRE; it
is also strongly connected to the banking systems in other Nordic-Baltic countries where there
are also RRE-related risks to financial stability. The Finnish authorities have applied several
banking capital measures and an LTV limit was set through a legislative amendment in July
2016; however, the macroprudential authority currently lacks powers to implement certain
measures such as LTI, DTI and DSTI ratio limits. For these reasons, the policy stance is
assessed as appropriate and expected to be sufficient with respect to the collateral and
banking stretches; however, it may not be sufficient for the household stretch.
•

Luxembourg: the main vulnerability is considered to be the combination of high RRE prices
and increasing household indebtedness. The collateral stretch is driven by a steady increase
in RRE prices in recent years, which has brought prices to an unprecedentedly high level.
These price developments have been sustained by a structural imbalance between strong
housing demand - fuelled, inter alia, by both demographic factors and policy incentives – and
supply-side limitations in terms of the availability of housing. Vulnerabilities in the household
stretch are signalled by rising levels of household mortgage debt relative to disposable
income. On average, the LTV and DSTI ratios in Luxembourg’s mortgage market are robust
and this is a mitigating factor. However, the distribution of the LTV and DSTI ratios for both
new and existing mortgages suggests that there is a noticeable share of loans with high LTV
and DSTI ratios, which could lead to negative direct and indirect effects on financial stability in
the event of economic or financial shocks. Moreover, mortgages in Luxembourg
predominantly have variable rates. Measures have been taken to address banking stretch and
these are assessed as being sufficient. However, the policy stance for the collateral stretch is
not appropriate and not sufficient since no measures have been taken in this area. Also, for
household stretch, while the measure that has been taken is appropriate, it is not expected to
be sufficient given the nature of the vulnerabilities.

•

Malta: the main vulnerabilities associated with the RRE market in Malta relate to the
household and collateral stretches. Growth of household debt is rapid and mainly driven by an
increase in mortgage debt. Malta has a relatively high debt level and debt service burden
compared with other countries. At the same time, RRE prices have increased noticeably in
recent years and now exceed their highest levels reached before the 2007-08 financial crisis.
While some vulnerabilities relating to household and collateral stretches have been identified
in Malta, these are mitigated by several factors and are assessed not to present systemic
risks at present. Furthermore, there are no impediments in national law hindering a rapid
deployment of borrower-based measures should vulnerabilities increase. It is important that
the Maltese authorities continue to monitor developments and analyse more granular data on
the distribution of household indebtedness.

•

The Netherlands: the main vulnerabilities are considered to be the persistently high
household debt levels combined with low mortgage collateralisation. In particular, there is a
large group of households, especially younger mortgagors, which have debt levels that
exceed the value of their home (one-quarter of homeowners and around 50% of first-time
buyers). While most of the risk indicators have moved in the right direction in recent years,
aggregate data show that the Dutch DTI, debt-to-GDP and LTV ratios are still among the
highest in Europe, but credit growth is currently not very rapid. Moreover, RRE prices are
increasing and are approaching previous peak levels. The measures that have been
introduced are being tightened at a slow pace over a long time horizon, which may not be fully
sufficient given the current level of risks. Thus the current policy stance is assessed as
appropriate, but is not expected to be sufficient in addressing vulnerabilities in the household
and collateral stretches. While the policy measures taken for the Netherlands are appropriate

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Executive summary

5

given the nature of RRE vulnerabilities, they may not be sufficient to fully address household
and collateral stretch vulnerabilities since most measures are only being gradually phased in
and their calibration will not be very constraining even after full implementation.
•

Slovakia: the main vulnerabilities in the Slovakian RRE market are related to the collateral
and household stretches. In particular, rapid credit growth (albeit from low levels) may signal
rising vulnerabilities from the household stretch and could lead to a build-up of excessive
household indebtedness in the future. In addition, RRE prices have been picking up since
early 2015 which, in combination with the increasing debt, suggests increasing risks of
collateral stretch. There had been signs of relaxing credit standards in recent years, although
recently the share of new loans with high LTV ratios has been decreasing. Overall, given that
the identified RRE-related vulnerabilities are assessed to be low although increasing, the
proactive policy stance in Slovakia is assessed as being appropriate and is expected to be
sufficient to curb a future build-up in vulnerabilities. The policy measures that have been taken
by the Slovakian authorities have already had an impact in reducing vulnerabilities.

•

Sweden: the main vulnerabilities are considered to be the increasing RRE prices that appear
to be overvalued, and high and increasing indebtedness especially among some groups of
households. In addition, if risks were to materialise, there may be potential spillover effects on
other countries in the Nordic-Baltic region. High and rising debt-to-disposable income ratios
and loans for house purchases indicate that vulnerabilities are building up in relation to
household stretch. Also, the collateral stretch is highlighted by the prolonged and continuous
increase in RRE prices – price growth has slowed down in the past six months, but Sweden
remains one of the most overvalued countries in Europe in terms of RRE. While the current
policy measures are appropriate given the nature of RRE vulnerabilities in Sweden, they may
not be sufficient to fully address the household and collateral stretches. Given that the
measures apply only to new housing loans, it will take time for the vulnerabilities related to the
level of household indebtedness to substantially decrease. Tools that could directly address
the high debt relative to income are not in place; this is related to the fact that the mandate of
the Swedish macroprudential authority is unclear with respect to some measures.
Furthermore, the high and overvalued RRE prices are not directly addressed by current policy
measures.

•

The United Kingdom (UK): there is currently a high degree of uncertainty about the mediumterm outlook for the UK housing market, which may be at a turning point following the UK’s
referendum on European Union (EU) membership on 23 June 2016. Before the referendum,
the main risks related to the interaction of a household stretch (due to household
indebtedness) and a collateral stretch (as indicated by RRE prices that were rising from
already elevated levels and decoupling from rent and income growth rates). After the
referendum, the outlook for the UK economy and housing market has been revised down. If
that forecast proves to be correct, it would slow the pace of build-up in mortgage debt and
therefore reduce vulnerabilities in the medium term. But an economic slowdown could lead to
the crystallisation of some risks – e.g. if unemployment rises and/or income growth falls, then
some households may find it more difficult to service their debts. However, it is also possible
that the slowdown in the housing market could prove to be temporary and, after a pause, RRE
prices, mortgage approvals and household debt could begin to grow again. In this scenario,
vulnerabilities related to residential real estate would continue to rise. The appropriateness
and sufficiency of the policy stance in the UK has not been directly assessed given the high
degree of uncertainty about the medium-term outlook for the UK housing market. The
appropriate policy response will be scenario-dependent. Therefore, it will be important for the
UK authorities to monitor developments closely and adjust macroprudential policy in light of

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Executive summary

6

them. Looking ahead, it will be necessary to ensure that any adjustment in the housing market
proceeds at an appropriate pace and that new vulnerabilities do not emerge.
Based on the final assessments for the focus countries, the ESRB has identified in eight
countries certain medium-term vulnerabilities as a source of systemic risk to financial
stability, which may have the potential for serious negative consequences for the real
economy. These are: Austria, Belgium, Denmark, Finland, Luxembourg, the Netherlands, Sweden
and the United Kingdom. On the basis of this analysis, on 22 September 2016 the ESRB General
7
Board adopted eight warnings to these countries about medium-term vulnerabilities in their RRE
sectors.
The remainder of the report is structured as follows:
•

Section 1 discusses the importance of RRE to the economy and for macroprudential policy as
discussed in the literature;

•

Section 2.1 presents the EU-wide analysis which identified the set of focus countries;

•

Section 2.2 presents the approach to country-specific analysis and the assessments for the
eleven focus countries; and

•

Conclusions.

The analysis in this report reflects available data and known developments up to mid-September
2016.

Table E.1
Summary assessment and analysis: focus countries
Please find the table on the following four pages
*Appropriate policy measures are those assessed to be conceptually suitable given the nature and timing of risks; sufficient policy measures are ones
that are expected to or can be shown to significantly mitigate, or reduce the build-up of, risks over an appropriate time horizon with a limited
unintended impact on the general economy.
Notes: For an overview of the results and methodology for the horizontal risk analysis, see Section 2.1 and Annex B. For an overview of the policy
assessment including definitions of the terms “appropriate” and “sufficient”, see Section 2.2.1.

7

In order to contribute to the prevention or mitigation of systemic risks to financial stability in the European Union, the ESRB
shall issue warnings when significant systemic risks are identified. (Regulation (EU) No 1092/2010, as above fn. 2). The
eight warnings are available on the ESRB website, they are numbered as follows: ESRB/2016/05 (Austria); ESRB/2016/06
(Belgium); ESRB/2016/07 (Denmark); ESRB/2016/08 (Finland); ESRB/2016/09 (Luxembourg); ESRB/2016/10 (the
Netherlands); ESRB/2016/11 (Sweden); and ESRB/2016/12 (the United Kingdom).

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Executive summary

7

Country

AT

BE

DK

Key vulnerabilities

Stretches

• Vulnerabilities for Austria are related to robust growth, particularly recently, in RRE prices
and mortgage credit and the risk of a further loosening in lending standards.
• RRE prices are increasing rapidly, in particular since 2011. In Q1 2016, RRE prices
increased by 8.9% (year-on-year) in Austria outside Vienna and by 6.5% in Vienna, and are
now above the pre-crisis level in Austria.
• Overall, RRE prices in Austria are broadly in line with fundamentals, but have increased
quickly relative to some fundamentals (e.g. the PTI ratio increased by 27% between Q1
2010 and Q1 2016). At the same time, RRE prices in Vienna appear to be above
fundamentals (by 22.8% in Q1 2016) according to OeNB models.
• Housing credit is growing robustly (loans for house purchase grew by 5% in June 2016
over the year). At the same time, the first indications, which must be interpreted with care, of
an OeNB survey indicate a decline in lending standards.
• The related data suggest that the sample average median DTI ratio among surveyed banks
increased to 490% in Q4 2015 from around 400% in Q4 2014 for new mortgages, while the
sample average median LTV ratio for new mortgages increased to 65% in Q4 2015 from
60% in Q4 2014. However, the share of the volume of new loans with LTV ratios above 90%
increased between Q1 2013 – Q2 2014 and Q3 2014 – Q4 2015. Furthermore, 67% of the
volume of new loans had a DTI ratio above 400% in Q4 2015. Given the available evidence,
the DSTI ratio has been stable.
• The share of variable rate and foreign currency mortgages in the stock of loans is still
significant despite declining.

• collateral

• The main RRE-related vulnerability in Belgium is related to the fast increase in overall
household indebtedness, combined with significant groups of already highly indebted
households, against the background of a significant increase in RRE prices over the past
few years. Lending for house purchases has been rapidly increasing, with an annual
increase of 8.1% in June 2016 (5.3% when corrected for securitisation operations).
• At the same time, groups of households are highly indebted, with high DSTI ratios including
for new loans (more than 20% of loans have a DSTI ratio at origination above 50% and
almost 20% of new loans have a DSTI above 50%, and one-third of loans have LTV ratios
above 90%).
• RRE prices have increased significantly over the past 30 years (a 4% increase in 2015)
and have been increasing faster than incomes or rents in recent years. In nominal terms,
RRE prices are now close to their level prior to the financial crisis. There are some signs of
price overvaluation, but alternative valuation models do not demonstrate this unequivocally.
• There are low risk weights (10%) for mortgage loans of banks using IRB models (before
the 5 p.p. add-on).

• banking

• The main vulnerabilities are considered to be the robustly increasing RRE prices – in
particular in the major cities – in combination with highly indebted households. In addition, if
risks were to materialise, there could be potential spillover effects on other countries in the
Nordic-Baltic region.
• Households’ debt levels are very high both relative to income (the average DTI ratio is
263%) and to GDP (123%). Debt is particularly high for some households (25% of
homeowners have DTIs above 300% and 30% of homeowners have total debt of more than
100% of the value of their house).
• RRE prices are increasing, driven by fast increases in major cities where they are
approaching pre-crisis levels (house prices increased annually by 3.5% in the whole of
Denmark in Q1 2016 and by 10.4% in Copenhagen).
• Even though the overall credit growth does not appear to be fast, mortgage credit
institutions are increasing lending in the major cities, which is coupled with rapid price
increases.
• High proportion of interest-only loans (50%) and variable rate loans (60%).

• collateral

• household

• collateral

Assessment:
Appropriateness &
Sufficiency of
policies*

ESRB
Warning
issued?

Appropriate but not
expected to be
sufficient

Yes

Policy stance is appropriate but not expected to be sufficient for collateral
and household stretches
• While the policy measures that have been taken by the Austrian authorities are
appropriate given the nature of RRE vulnerabilities in Austria, they may not be
sufficient to fully address them.
• Despite the measures taken, RRE prices and mortgage credit are growing
robustly, there are groups of households with elevated debt levels and there is
some evidence of weakening lending standards.
• Even though soft measures have been taken and steps have been taken to
make policy instruments legally available, there is a lack of borrower-based
macroprudential tools in the law. These measures could effectively prevent an
excessive build-up of vulnerabilities and systemic risk.
• The measures taken for the banking stretch seem sufficient to deal with RRE
vulnerabilities relating directly to the banking system. However, given the
developments in RRE prices and credit, the measures taken for the collateral and
housing stretches may not be sufficient. Appropriate measures have been taken
for all stretches.

Appropriate but not
expected to be
sufficient

Yes

Policy stance is appropriate but not expected to be sufficient for collateral
and household stretches
• Measures directly addressing the vulnerabilities related to highly indebted
households or the continued increase in RRE prices have not been adopted.
• Furthermore, the trend of tightening lending standards appears to have ended,
which – together with very high credit growth – indicates that vulnerabilities could
be building up.
• The add-on of 5 p.p. to risk weights is deemed sufficient to address the banking
system stretch.
• While the policy measures that have been implemented are appropriate given
the nature of RRE vulnerabilities in Belgium, they may not be sufficient to fully
address them.

Appropriate but not
expected to be
sufficient

Yes

Policy stance is appropriate but not expected to be sufficient for collateral
and household stretches
• While the policy measures taken are appropriate given the nature of the RRE
vulnerabilities in Denmark, they may not be sufficient to fully address them. Even
though mortgage lenders have themselves reported a tightening in lending
standards, this has not yet had a noticeable impact on the level of household
indebtedness or real estate prices – on the contrary, both credit and prices are still
increasing in the major cities. In the light of the RRE price increases, particularly
in the main cities, there is a risk that these developments could lead to a further
increase in household indebtedness.
• Moreover, the high level of household debt is not expected to significantly
decline since it is not directly addressed by these policies. It is important to note
that this assessment reflects the fact that some of the measures have only been
in effect for a limited period of time and are entering into force gradually, while
some of them only affect new borrowers.
• Vulnerabilities related to the high proportion of interest-only loans and variable
rate loans seem to be sufficiently addressed by microprudential regulation.

• household

• household

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Executive summary

Reasoning behind assessment

8

Country

Assessment:
Appropriateness &
Sufficiency of
policies*

ESRB
Warning
issued?

Key vulnerabilities

Stretches

EE

• Rapidly increasing RRE prices that are close to their pre-crisis peak levels suggest that
vulnerabilities are building up in the collateral stretch (since Q1 2009 real property prices
have increased by more than 50%). However, recently, there appears to be some
stabilisation in RRE prices.
• Furthermore, RRE price increases have been supported by income growth which may not
be sustainable in the long run since it has outpaced productivity growth.
• Risks and vulnerabilities in the household and banking stretches appear more contained,
owing to relatively low indebtedness of the household sector, moderate growth in RRE
lending and high capital adequacy of the banking sector.
• The Estonian economy is, however, exposed to risks in the global economy and the
banking sector is structurally vulnerable due to its high degree of concentration and
interconnectedness, in particular with the Swedish banking system. International risks could
spill over to Estonia through both credit supply and trade channels.

• collateral

Appropriate and
expected to be
sufficient

No

The policy stance is appropriate and expected to be sufficient
• The Estonian authorities have implemented a combination of precautionary
policy measures to prevent RRE lending standards from loosening from their
current level and to increase the resilience of the banking sector to structural
vulnerabilities in the Estonian economy and financial sector.
• Given the comprehensive set of precautionary policy measures aimed at all
three stretches, the policy stance is assessed as appropriate.
• The measures are also expected to be sufficient given the current level of and
trend in vulnerabilities. Nevertheless, the policy stance is forward looking and the
measures taken should reduce the misalignment of incentives that could lead
banks to issue an excessive number of mortgages in future or households to take
on an excessive amount of housing debt.

FI

• The main vulnerabilities are high and increasing household indebtedness, especially
among some groups of households. In addition, if risks were to materialise, there could be
potential spillover effects on other countries in the Nordic-Baltic region.
• Households’ debt levels are relatively high in Finland: the DTI ratio is relatively high at
112% as is the debt-to-GDP ratio at 66%.
• More concerning are the groups of highly indebted households: 10% of households have
DTI ratios above 300% and these households account for almost half of total household
debt.
• In addition, households appear to be exposed to interest rate risks, since more than 95% of
new and existing mortgage loans have variable interest rates.
• Price indicators suggest that prices relative to income and rents are close to their long-term
average; however, given the weak economic outlook, the likelihood of a manifestation of
RRE risks over the short-to-medium term is elevated.
• The banking sector is concentrated with large exposures to RRE and is very
interconnected with the Nordic banking system and, to some extent, reliant on market
funding. Also, the potential direct risks to the banking and financial system could be
significant if they were to materialise, especially given the size of the mortgage market in
relation to the banking system and the overall economy.

• banking

Appropriate but not
expected to be
sufficient

Yes

Policy stance is not expected to be sufficient for the household stretch
• While the measures taken are deemed appropriate and conceptually suitable
given the nature of risks, it is not clear that they will significantly mitigate
vulnerabilities related to the household stretch (in particular, the high overall
indebtedness of households and the large share of highly indebted households).
• The recently introduced LTV measure and the planned floor for IRB banks’ risk
weights are expected to indirectly contribute to a reduction of household stretch,
but macroprudential measures such as LTI, DTI or DSTI limits would be more
effective in preventing a further rise in the number of highly indebted households
(it should also be noted that the introduced LTV measure will only affect new
borrowing).
• The situation is further complicated by the fact that the Finnish authorities lack
the legal instruments to implement certain measures such as LTI, DTI and DSTI
limits, preventing them from directly addressing vulnerabilities in the household
stretch in the short-to-medium term.
• On the other hand, the gradual reduction of mortgage interest tax subsidies is
an important policy change impacting households’ incentives and going in the
right direction.
• While these policy measures are expected to be sufficient for the collateral and
banking stretches, they may not be sufficient for the household stretch.

• The main vulnerabilities are considered to be the combination of high RRE prices and
increasing household indebtedness.
• Prices are currently at an unprecedentedly high level, and are increasing both in relation to
income and the level of rents (in Q1 2016 nominal prices increased 4.5% annually, the PTI
index increased by 6 p.p. annually and the PTR index increased by 4 p.p. annually). These
price developments have been sustained by structural factors.
• Regarding household indebtedness, the latest DTI figure suggests that debt is high (the
DTI was 149% in Q1 2016), while the debt-to-GDP ratio appears to be more muted at 57%
in Q1 2016.
• On average, the LTV and DSTI ratios in Luxembourg’s mortgage market are robust and
represent a mitigating factor. However, the distribution of the LTV and DSTI ratios both for
new and outstanding mortgages suggests that there is a notable share of loans with high
LTV and DSTI ratios that could lead to negative direct and indirect effects on financial
stability in the event of economic or financial shocks. Moreover, household debt for house
purchases is increasing rapidly (an annual growth rate of 6% in June 2016).
• The majority of mortgages are variable rate loans (on average between May 2015 and May
2016, 52% of new loans had variable rates).

• collateral

Not appropriate and
not sufficient

Yes

Policy stance is not appropriate and not sufficient for the collateral stretch,
and appropriate but not expected to be sufficient for the household stretch
• Given the level and dynamics of identified vulnerabilities, the policy stance
regarding the RRE sector in Luxembourg is deemed not appropriate, and
therefore also not sufficient, due to a lack of policy measures to address collateral
stretch.

LU

• collateral
• household

• household

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Executive summary

9

Reasoning behind assessment

Country

MT

NL

SK

Key vulnerabilities

Stretches

• The rapid growth of households’ total debt due to robust mortgage growth, and the
relatively high debt level and debt service burden in relation to households’ income.
• During the first half of 2016 mortgage growth decelerated somewhat, but remained rapid at
6.6%. Total financial liabilities of households constituted approximately 70% of GDP in 2015,
which is the euro area average. However, total financial liabilities in comparison to wages
(compensation of employees) were significantly higher in Malta than in the euro area, and
reached nearly 160% (the euro area average is around 140%). The debt service-to-income
ratio is relatively high in Malta (at 13%) despite the currently prevailing low level of interest
rates. However, using the Central Bank of Malta estimates for disposable income, the DSTI
ratio for the corresponding period goes down to 9.3%.
• In terms of collateral stretch, the official transaction-based RRE price data showed 2.6%
annual growth, whereas advertised prices rose by 9.9% in Q1 2016. Both price indices have
passed their peaks reached before the last financial crisis, by 1.4% and 16.7% respectively.
Different RRE price valuation methods indicate that, on average, real estate prices in Malta
are broadly in line with fundamentals.

• collateral

• The main vulnerabilities are considered to be the persistently high household debt levels
combined with low mortgage collateralisation. In particular, there is a large group of
households, especially younger mortgagors, which have debt levels that exceed the value of
their home.
• Household debt levels are very high both in comparison with income (the DTI ratio is
231%), GDP (111%) and house values (the LTV ratio is 94% for new loans and 68% for the
stock), despite risk indicators having improved in recent years.
• Total mortgage lending to households by banks and all other institutions granting mortgage
loans has been muted at 1.1%, whereas growth in lending to households by MFIs has been
higher at 4% over the last year.
• A quarter of homeowners and around 50% of first-time buyers have total debt in excess of
the value of their property.
• RRE prices in the cities are approaching peak levels and overall RRE prices in mid-2016
increased by 4.4% annually.

• collateral

• Rapid credit growth (credit for house purchases increased by 14% year-on-year in Q2
2016), albeit from low levels, in Slovakia may signal rising vulnerabilities in the household
stretch.
• The credit growth is linked to financial deepening in Slovakia, but could potentially lead to a
situation of excessive household indebtedness.
• There are some signs of household stretch: a high share of households is vulnerable to
interest rate increases due to short interest rate fixation periods.
• Furthermore, RRE prices have been picking up since early 2015, which in combination with
increasing debt suggests increasing vulnerabilities in the collateral stretch. Overall, RRE
prices do not appear to be overvalued.
• There has been a tendency to relax lending standards in recent years, but this has
somewhat reversed in response to policy measures that have been implemented. There is a
practice of “top-up financing” where the fall in the DSTI ratio due to the low interest rates is
being taken advantage of to increase the level of household debt.

• collateral

• household

• household

• household

Assessment:
Appropriateness &
Sufficiency of
policies*

ESRB
Warning
issued?

Appropriate and
expected to be
sufficient

No

Policy stance is appropriate and expected to be sufficient
• Overall, the policy stance is considered to be appropriate and expected to be
sufficient in Malta at present given the current level of risks from the RRE sector.
• While some vulnerabilities relating to the household and collateral stretches have
been identified in Malta, these are mitigated by several factors and are assessed
not to present systemic risks at present. There are no impediments in national law
hindering a rapid deployment of borrower-based measures should vulnerabilities
increase.
• A number of micro- and macroprudential measures have been taken to address
direct risks to the banking sector stemming from RRE vulnerabilities. These are
assessed as appropriate and expected to be sufficient, particularly given the high
capitalisation of the banking system and high risks weights applied to RRE
exposures.
• It is important that the Maltese authorities continue to monitor the evolution of
RRE prices and lending standards due to rapid mortgage growth, and that they
ensure access to and analyse more granular data with respect to household
stretch.

Appropriate but not
expected to be
sufficient

Yes

Policy stance not expected to be sufficient for collateral and household
stretches
• Measures are only being gradually tightened at a slow pace over a long time
horizon.
• Even after full implementation, the LTV limit (100% in 2018) and tax deductibility
will still be high.
• While the policy measures taken for the Netherlands are appropriate given the
nature of RRE vulnerabilities, they may not be sufficient to fully address them as
most measures are only being gradually phased in and their calibration will not be
very constraining even after full implementation.

Appropriate and
expected to be
sufficient

No

The policy stance is appropriate and expected to be sufficient
• Overall, given that the identified RRE-related vulnerabilities are assessed to be
low although increasing, the proactive policy stance in Slovakia is assessed as
being appropriate and expected to be sufficient to curb a future build-up in
vulnerabilities.
• There is evidence that the policy measures have already been quite effective,
e.g. in stopping a decline in lending standards. In addition, the move to transpose
the current recommendations into decrees and to tighten some of the limits should
further increase their effectiveness.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Executive summary

Reasoning behind assessment

10

Country

SE

UK

Key vulnerabilities

Stretches

• The main vulnerabilities are considered to be the rapidly increasing RRE prices which
appear to be overvalued, and high and increasing indebtedness especially among some
groups of households. In addition, if risks were to materialise, there could be potential
spillover effects on other countries in the Nordic-Baltic region.
• High and rising debt-to-disposable income ratio for households with new loans (406% in
2015, up from 387% in 2014).
• Credit growth has been rapid (loans to households for house purchases have increased by
8.7% year-on-year in June 2016).
• A prolonged and continuing increase in RRE prices (by 12% in 2015), which has however
slowed down during the last six months.
• RRE prices are, according to the ECB model, the most overvalued in Europe, though the
IMF model shows less overvaluation.

• collateral
• household

• There is currently a high degree of uncertainty about the medium-term outlook for the UK
• collateral
housing market. From a macroprudential perspective, there appear to be risks under
different scenarios for the housing market – either through the crystallisation of accumulated • household
vulnerabilities, particularly related to household indebtedness and the interaction with
elevated RRE prices, or through the further build-up of vulnerabilities.
• RRE vulnerabilities had built up before the referendum – they related to the interaction of a
household stretch (due to household indebtedness) and a collateral stretch (as indicated by
RRE prices that were rising from already elevated levels and decoupling from rent and
income growth rates).
• The UK residential real estate market is potentially at a turning point. Given the uncertainty
of the implications of the UK’s referendum on EU membership, it is not yet possible to judge
whether the vulnerabilities that had accumulated will now begin to crystallise or whether, in
time, they might instead continue to grow.
• The outlook for the UK economy and housing market has been revised down: the Bank of
England expected in its August Inflation Report aggregate RRE prices to decline a little over
the next year, and the level of mortgage approvals to be lower. If that forecast proves to be
correct, it would slow the pace of build-up in mortgage debt and therefore reduce
vulnerabilities in the medium term. However, an economic slowdown could lead to the
crystallisation of some risks – for example, if unemployment rises and/or income growth falls,
then some households may find it more difficult to service their debts.
• However, it is also possible that the slowdown in the housing market could prove to be
temporary and, after a pause, RRE prices, mortgage approvals and household debt could
begin to grow again. In this scenario, vulnerabilities related to residential real estate would
continue to rise.

Assessment:
Appropriateness &
Sufficiency of
policies*

ESRB
Warning
issued?

Appropriate but not
expected to be
sufficient

Yes

Policy stance is not expected to be sufficient for collateral and household
stretches
• The current policy measures are appropriate given the nature of RRE
vulnerabilities in Sweden, but they may not be sufficient to fully address them.
• Given that the measures apply only to new housing loans, it will take time for the
vulnerabilities related to the level of household indebtedness to substantially
decrease.
• The lack of tools is related to the fact that FI’s mandate remains unclear with
respect to some measures.
• Furthermore, the high and somewhat overvalued RRE prices have not been
directly addressed.

Not directly assessed
given the uncertain
impact of the vote to
leave the EU on the
medium-term outlook
for the UK housing
market.

Yes

Not directly assessed given the uncertain impact of the vote to leave the EU
on the medium-term outlook for the UK housing market
• But it is considered that, although the build-up of risk through the household
income and collateral stretch channels appears to have abated, the probability of
risks through these channels materialising has increased in the short-to-medium
term, given the increased level of uncertainty and the lower economic growth
projections.
• Conversely, it is also possible that the slowdown in the housing market could
prove to be temporary and, after a pause, RRE prices, mortgage approvals and
household debt could begin to grow again. In this scenario, vulnerabilities related
to residential real estate would continue to rise.
• The appropriate policy response is likely to differ between these two scenarios.
Therefore, it will be important for the UK authorities to monitor developments
closely and adjust macroprudential policy in light of them. Looking ahead, it will be
necessary to ensure that any adjustment in the housing market proceeds at an
appropriate pace and that new imbalances do not emerge.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Executive summary

Reasoning behind assessment

11

Section 1
Addressing vulnerabilities in residential real estate: a
key task for macroprudential policymakers

1.1

The importance of residential real estate in the economy and for
macroprudential policy

Housing is a key sector in the real economy and represents a major part of household
wealth. The residential real estate (RRE) market is among the most important sectors of the
economy. Housing represents a major part of households’ wealth and constitutes a major source of
collateral for lenders. Mortgages often make up large parts of banks’ balance sheets, and account
for the largest and most common form of debt among households. Furthermore, housing
construction is typically an important component of the real economy, as a source of employment,
investment and growth (see Chart 1.1).
Excessive risk-taking, leverage and misaligned incentives in RRE may lead to externalities
with implications for financial stability and the real economy. The importance of the housing
market for the real economy implies that the key actors in this market – households, construction
companies and banks/lenders – do not bear the full economic consequences of their behaviour,
and that there are potential important externalities for the real economy. Since the economic agents
do not consider these spillovers, they tend to take risks that are excessive from society’s point of
view.
The interaction of various social and economic policies has a strong impact on housing
market dynamics and vulnerabilities. The housing market is strongly influenced by social and
economic policies. It is indeed one of the most regulated sectors, where multiple policy objectives –
such as the availability and affordability of housing, safety and health regulation, environmental
regulation, spatial planning, etc. – interact to produce distinct national differences. This vast array of
regulatory policy interactions may further skew the incentives for risk-taking among key actors, for
instance where tax systems subsidise indebtedness. Also, monetary policy plays a key role by
influencing interest rates and margins charged on mortgages, which not only affect bank profitability
(and thereby capital levels) and household expenses, but may also transmit into RRE price
dynamics. Implicit or explicit subsidies and guarantees for the various actors in the RRE market
8
may further skew incentives and influence RRE prices.

8

This could include, for example, systemically important entities or markets directly or indirectly related to RRE (e.g. if
mortgage exposures are concentrated in a few domestically systemic banks, or if there a covered bond market of high
importance to the domestic financial system).

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Addressing vulnerabilities in residential real estate: a key task for macroprudential policymakers

12

Chart 1.1
Importance of RRE for households, banks and the real economy
a) Credit for house purchase

b) Mortgage loans

(% of annual nominal GDP, Q1 2016)

(% of banks’ Common Equity Tier 1, Q4 2015)

DK
CY
SE
NL
UK
PT
ES
LU
MT
FI
FR
GR
DE
BE
EE
IE
AT
SK
IT
CZ
PL
LV
LT
HR
SI
BG
HU
RO

DK
SE
NL
ES
FI
BE
SK
PT
LT
IT
PL
IE
CY
CZ
RO
GR
FR
EE
AT
MT
LV
HR
SI
DE
LU
0

20

40

60

80

100

120

0

100

200

300

400

500

600

700

c) Employment in construction and real estate
activities

d) Value added (gross) by construction and real
estate activities

(percentage)

(percentage of GDP)

EE
LV
SK
AT
LT
CZ
PL
UK
SE
FR
FI
BE
RO
CY
BG
DK
HR
DE
IT
IE
HU
PT
ES
MT
SI
NL
GR

GR
IT
LV
FI
FR
UK
ES
RO
AT
PT
EE
DE
SE
DK
HR
BE
BG
LT
CY
CZ
PL
LU
SI
HU
NL
MT
0

2

4

6

8

10

12

0

2

4

6

8

10

12

14

16

18

Sources: a) ECB Statistical Data Warehouse (SDW), Eurostat and ECB/ESRB Secretariat calculations. b) ECB SDW and ECB/ESRB Secretariat
calculations.c) ECB SDW, Eurostat and ECB/ESRB Secretariat calculations. d) Eurostat and ESRB Secretariat calculations.
Notes: a) Credit for house purchase is total lending for house purchase by monetary financial institutions (MFIs) to domestic households.
b) Mortgage loans are loans collateralised by immovable property on a consolidated basis. The ratio for Denmark if domestic mortgage credit
institutions are included stood at 469% in Q1 2016.
c) As a share of total employed persons (15 years and over) on average in the four quarters of 2015.
d) Seasonally and calendar-adjusted data as an average over the four quarters of 2015.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Addressing vulnerabilities in residential real estate: a key task for macroprudential policymakers

13

National macroprudential authorities and the ESRB have a responsibility to contribute to
preventing the build-up of financial stability risks in different sectors of the financial system
and the economy. Given the importance of RRE for financial and macroeconomic stability,
analysing vulnerabilities in housing markets across countries is a key responsibility of
macroprudential authorities. Taking a forward-looking approach and seeking to prevent the build-up
of vulnerabilities is especially important. At the EU level, the ESRB has a mandate to “[…]
contribute to ensuring financial stability and mitigating the negative impacts on the internal market
9
and the real economy”. Similar mandates are given to macroprudential authorities across countries
10
in the EU. Careful macroprudential monitoring and analysis of real estate-related vulnerabilities is
particularly warranted at this juncture, given the low interest rate environment across the EU. This
message has been repeated several times by the ESRB General Board and other influential bodies
11
in the area of macroprudential policy.
To fulfil this responsibility, the ESRB has analysed the vulnerabilities across EU countries
12
relating to the RRE sector. The ESRB has investigated whether there are vulnerabilities related
to the RRE sector in EU countries that may be a direct or indirect source of systemic risk to
financial stability, and may also have the potential for serious negative consequences for the real
economy. The results of the vulnerability assessment of the EU RRE sector are presented in this
report.

1.2

The nature and effects of financial crises relating to residential real estate

Residential real estate markets are prone to “boom/bust” cycles. While RRE markets often
display considerable stability over long periods of time, they have also recurrently been prone to
boom/bust cycles with detrimental effects on financial stability and the real economy. These cycles
are typically characterised by reinforcing and procyclical patterns in price developments and risk13
taking among lenders and borrowers.
Vulnerabilities accumulate in the upturn. In the boom phase, strong labour markets, optimistic
outlooks and abundant credit feed into high demand, which tends to push real estate prices higher.
Price increases lower credit risk by raising collateral values, and may also create expectations of
further price increases, feeding back into higher demand. Potential relaxation of lending standards
may also fuel the boom – particularly in the current low-yield environment where interest rate
margins are under pressure and banks may be tempted to make up for lower margins by increasing

9

Recital 10, Regulation (EU) No 1092/2010, as above fn. 2.

10

For an overview, see for instance Buiter, W., “Housing wealth isn’t wealth”, Economics - The Open-Access, Kiel Institute for
the World Economy, Vol. 4(22), 2010, pp. 1-29; Jordà, O., Schularick, M. and Taylor, A., “Leveraged Bubbles”, Journal of
Monetary Economics, Vol. 76, pp. S1-S20.

11

The press release of the ESRB General Board of 24 September 2015 emphasises that the “[…] global environment of low
interest rates and low risk premia, while necessary to support the still sluggish nominal growth, is one common driver of the
current risk situation and may have unintended effects on some economic sectors or in some countries that may require the
adoption of targeted macroprudential measures”. Similarly, the article entitled “The state of the house price cycle in the
euro area”, Economic Bulletin, Issue 6, ECB, 2015 (hereafter "ECB 2015a"), states that price growth in residential real
estate needs monitoring, especially when accompanied by increased leverage, against the backdrop of the current
accommodative monetary policy.

12

An ESRB task force was created to undertake this analysis. Participants in the task force are shown in the list of
Participants, above. See Annex A for an overview of the teams including their mandates and main forms of interaction.

13

Buiter, W. (2010) as above fn. 10; Jordà et al. (2015) as above fn. 10.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Addressing vulnerabilities in residential real estate: a key task for macroprudential policymakers

14

volumes. Such reinforcing spirals encourage debt accumulation among households, risk-taking
among banks and, in some cases, booms in the construction sector.
Housing downturns can have both direct and indirect effects on financial stability and the
real economy. Whereas the underlying causes and triggers may differ, bust phases in RRE
markets are characterised by the opposite developments to the boom phase. First, price drops
lower collateral values, which in turn increase the losses that lenders face in the event of a default.
Second, household wealth and the prospects of the construction sector are negatively affected,
which tends to affect their spending and investment behaviour. This reduces overall economic
activity, leads to deteriorating macroeconomic conditions and weakens the outlook and fiscal
balances. This in turn reduces lenders’ willingness to provide credit and increases the risk of
borrower defaults. These negative feedback loops may thus lead to losses, both among lenders
14
(direct effects) and in terms of economic output (indirect effects).
15

Financial crises relating to housing are relatively frequent and have severe repercussions.
RRE busts are common causes of banking crises and occur at relatively high frequency. The
consequences following an RRE bust are typically severe, not least given the importance of real
16
estate in the balance sheets of households and credit institutions. Despite the fact that the
financial sector is often offered public support – in the shape of crisis management and fiscal
expansion – in RRE crises, the effects on the capital and funding position of financial institutions
are typically material. While it is difficult to compile comparable information on these effects,
anecdotal evidence points to the severe repercussions in terms of reduced asset quality, credit
contraction and bank failures (see Table 1.1). Also, macroeconomic variables – such as
consumption, investment and employment – typically deteriorate significantly. Recessions following
RRE busts are common, and tend to be particularly deep and prolonged.

14

Direct losses could stem from reduced profitability as a result of provisions, higher impairment charges or an increased cost
of funding. These effects could be related to other balance sheet items than mortgages, such as shares in real estate
investment funds and venture capital funds exposed to RRE. For an extended discussion on direct and indirect effects, see
below Section 1.3.

15

See, for example, Emerging Horizons in Real Estate – An Industry Initiative on Asset Price Dynamics, World Economic
Forum, 2015, for country case studies; Reinhart, C. M. and Rogoff, K. S., “The Aftermath of Financial Crises”, American
Economic Review, Vol. 99(2), 2009, pp. 466-72, for global evidence; and Mian, A. and Sufi, A., House of debt: How they
(and you) caused the Great Recession, and how we can prevent it from happening again, University of Chicago Press,
2014, for the US sub-prime crisis.

16

For an illustration of how RRE-related crises have impacted real GDP growth, see ESRB 2015 and Hartmann, P., “Real
estate markets and macroprudential policy in Europe”, Working Paper Series, No 1796, ECB, 2015 (hereafter "ECB
2015b").

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Addressing vulnerabilities in residential real estate: a key task for macroprudential policymakers

15

Table 1.1
Overview: repercussions of RRE-related crises
Type of effect

Estimation/historical experiences

Source

Asset quality/credit risk

Following the global financial crisis, the
increase in bankruptcies was 8.9% on average
in countries with housing crises and 2% on
average in other countries.

“Report on Residential Real Estate”, ESRB
Expert Group on Real Estate, 2015

Bank failures/banking crises

2/3 of systemic banking crises have been
preceded by housing boom/bust patterns.
Also, in a sample of 51 boom/bust episodes, 35
were followed by a crisis.

Crowe, C., Dell’Ariccia, G., Igan, D. and Rabal,
P., “How to deal with real estate booms:
Lessons from country experiences”, Journal of
Financial Stability, Vol. 9(3), 2013, pp. 300-319

Economic growth

Output losses in recessions accompanied by
housing busts are two to three times greater
than in normal recessions.

Claessens, S, Kose, A. and Terrones, M.,
“What Happens During Recessions, Crunches,
and Busts?”, IMF Working Paper WP/08/274,
2008

Recessions associated with RRE price busts
are on average over a quarter longer than
those without busts.

Claessens, S, Kose, A., Terrones, M. (2008)

In a global sample of 78 house price booms, 49
ended up in recessions.

Cerutti, E., Dagher, J. and Dell’Ariccia, G.,
“Housing Finance and Real-Estate Booms: A
Cross-Country Perspective”, Staff Discussion
Notes No 15/12, International Monetary Fund,
2015

Among crisis-struck EU countries, GDP
declined by 2.4% in countries with real estate
problems, and increased by 0.4% for countries
without real estate problems, following the
global financial crisis.

“Report on Residential Real Estate”, ESRB
Expert Group on Real Estate, 2015

RRE price busts have on average been
associated with a 3.15% increase in the
unemployment rate.

Claessens, S, Kose, A. and Terrones, M.
(2008)

Employment

1.3

Analysing vulnerabilities in residential real estate: collateral, household
and banking stretches

A framework to analyse vulnerabilities in RRE that considers the levels of and dynamics in
RRE prices, as well as vulnerabilities related to lenders and borrowers, has been developed.
As demonstrated by the frequent boom/bust cycles of RRE markets and the associated financial
crises and economic downturns, a framework for analysing vulnerabilities in RRE markets must
consider dimensions relating to both RRE prices as well as the positions of lenders and borrowers.
Furthermore, to facilitate a more granular investigation of how policies and structural factors interact
with vulnerabilities, the analysis also looks at whether vulnerabilities are elevated, rising or both.
Indeed, macroprudential tools are best used to prevent the build-up of vulnerabilities and should in
17
this regard be forward-looking. The analytical framework adopted in this report – and developed
18
by the ECB/ESRB – distinguishes between collateral, household and banking stretches:
•

Collateral stretch: vulnerabilities relating to property markets, particularly in relation to a
sudden reversal in RRE price growth. Risks may crystallise through higher losses given
default (LGDs) for banks’ affecting their balance sheets or reduced household consumption,
with possible negative feedback effects to the financial system.

17

One objective of macroprudential policy is to increase resilience when risks are building up (see e.g. Borio, C., “Towards a
macroprudential framework for financial supervision and regulation?”, BIS Working Paper No 128, 2003).

18

These three stretches are introduced and discussed in ESRB 2015.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Addressing vulnerabilities in residential real estate: a key task for macroprudential policymakers

16

•

Household stretch: vulnerabilities related to borrowers’ indebtedness and ability to service and
repay debt. Vulnerabilities also relate to borrowers’ ability to maintain their consumption
pattern. A reduced consumption pattern could have negative feedback effects on housing
demand and prices, as well as on the general economy, leading to potential negative effects
on financial stability.

•

Banking stretch: vulnerabilities related to direct losses by banks or their loss of funding due to
their RRE exposures. The significance of lenders’ exposures and their perceived vulnerability
was considered in conjunction with measures of the lenders’ resilience.

For each of these stretches, a number of key indicators are identified based on their frequent
association with (the build-up of) vulnerabilities and subsequent RRE crises.
Interactions across stretches are amplifiers of RRE vulnerabilities. Vulnerabilities in merely
19
one stretch could constitute a source of concern (particularly for household and banking stretch),
but the existence of vulnerabilities across several dimensions is typically more problematic due to
the large interdependencies and tendencies for mutual reinforcements across them (or feedback
loops as discussed above). For instance, international empirical evidence suggests a strong link
between RRE prices and household debt. Similarly, a fall in consumption can in turn weigh on
wider economic stability, and loan performance in other sectors, thereby affecting banking
20
stretch. Also, decreasing RRE prices lower the value of collateral held by banks. Furthermore, it
is important to stress that RRE vulnerabilities often emerge from domestic structural features and/or
social and economic policies, such as tax deductibility, from cyclical developments or combinations
thereof.
Collateral stretch – price levels and dynamics in RRE markets: RRE price levels and dynamics
depend on several demand and supply-side factors. Per se, the level of RRE prices do not
constitute vulnerabilities to financial stability or the real economy, and are for this reason typically
not targets of macroprudential policy. However, large upswings in prices have often been followed
21
by periods of financial instability and/or recessions. This relates to the dynamics between levels
and expectations of prices, household wealth and credit risk. Housing is both a consumption good
and an investment good. Therefore, RRE prices are not only based on fundamentals, but also have
22
a speculative component. Persistent and large increases in RRE prices shape expectations of
future increases, thereby inducing households to take on additional debt or increase spending,
23
banks to issue additional credit, or construction booms. Persistent and large price increases also
heighten the risk of a sudden reversal in prices, which may lead to lower collateral values,

19

For instance, housing booms that are not credit-driven may still have large negative macroeconomic consequences.

20

See Section 3.2 in “The Financial Policy Committee’s powers over housing tools: A Policy Statement”, Bank of
England, July 2015.

21

Cerutti, E., Dagher, J. and Dell’Ariccia, G., “Housing Finance and Real-Estate Booms: A Cross-Country Perspective”,
Staff Discussion Notes No 15/12, International Monetary Fund, 2015.

22

Buiter, W. (2010) as above fn. 10; Benes, J., Laxton, D. and Mongardini, J., “Mitigating the Deadly Embrace in Financial
Cycles: Countercyclical Buffers and Loan-to-Value Limits”, IMF Working Paper WP/16/87, 2016.

23

Turk, R., “Housing Price and Household Debt Interactions in Sweden”, IMF Working Paper WP/15/276, 2015.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Addressing vulnerabilities in residential real estate: a key task for macroprudential policymakers

17

24

decreasing investment and oversupply. Such a reversal may also reduce household consumption
through wealth effects that vary both between households with different characteristics and across
25
countries. While this is particularly the case when households are indebted (which is typically the
case since most households need mortgages to be able to fund home purchases), negative
macroeconomic consequences from housing busts also occur when the housing boom has not
26
been credit fuelled (see Chart 1.2). Such corrections are also more likely when interest rates are
27
low. Indicators used to gauge the collateral stretch in the current horizontal risk identification and
the analytical framework include the price-to-income (PTI) ratio and a model-based overvaluation
28
measure developed by the ECB. Further indicators are used in the so-called vertical countryspecific analysis (see Section 2.2), including average LTV ratios and the share of amortising loans
29
and average maturity.

Chart 1.2
Housing busts and recessions: the role of credit
(percent (100x log))

Full sample, 1870–2013

Post-WW2 sample, 1948–2013

Source: Jorda, Schularick and Taylor (2015).
Notes: The solid blue line traces the average no-bubble path. The grey area represents the 90% confidence region around the average path. The
green dashed line is the sum of the average no-bubble path and the bubble coefficient when credit is below the mean, whereas the dotted red line is
the sum of the average no-bubble path and the bubble coefficient when credit is high. Full sample: 1870-2013, excluding the World Wars and a
window of five years around them. The y-axis shows the cumulative percentage change in real GDP per capita.

24

Developers’ price expectations, along with development lags, have been found to generate periods with significant
overbuilding (see Chinloy, P., “Real estate cycles and empirical evidence”, Journal of Housing Research, Vol. 7(2), 1996,
pp. 173-190; Grenadier, S. R., “The strategic exercise of options: development cascades and overbuilding in real estate
markets”, Journal of Finance, Vol. 51(5), 1996, pp. 1653-1679; Lee, G. S., “Housing cycles and the period of production”,
Applied Economics, Vol. 31(10), 1999, pp. 1219-1230; DeCoster, G. P. and Strange, W. C., “Developers, herding, and
overbuilding”, Journal of Real Estate Finance and Economics, Vol. 44(1), 2012, pp. 7-35.

25

This also occurs since lower prices make equity withdrawals more difficult (see Buiter, W., 2010 as above fn. 10).

26

Jordà et al. (2015) as above fn. 10.

27

Himmelberg, C., Mayer, C. and Sinai, T., “Assessing High House Prices: Bubbles, Fundamentals and Misperceptions”,
Journal of Economic Perspectives, Vol. 19(4), 2005, pp. 67-92.

28

For a description of the usefulness of the price-to-income ratio as an indicator of overvaluation of real estate markets, see
e.g. “Report on Residential Real Estate”, ESRB Expert Group on Real Estate, 2015, Section 2.1. For a detailed description
of the methodology, see Box 3 in Financial Stability Review, ECB, November 2015 (hereafter "ECB 2015c").

29

Included in Annex C.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Addressing vulnerabilities in residential real estate: a key task for macroprudential policymakers

18

Household stretch – implications of housing debt for households’ wealth and consumption:
a key transmission channel from the housing market to financial or economic instability occurs
through households. Empirical evidence suggests that when households have accumulated high
levels of debt or when they are highly leveraged, housing busts are more likely to end in costlier
30
and longer recessions. When households are leveraged, RRE price drops have particularly strong
31
effects on wealth and thereby consumption. Similarly, when debt service ratios are high, even
small income shortfalls can prevent households from consumption smoothing, while large income
32
shortfalls have been found to trigger increases in defaults and dampen the economic outlook. The
latter is likely to be particularly pronounced following long periods of low interest rates, especially in
33
cases where households rely extensively on variable rate mortgages. The risk of sharp
consumption reductions is particularly pronounced when high indebtedness interacts with sharp
falls in RRE prices. This relates to large wealth effects and increased leverage (as discussed in the
paragraph on collateral stretch). Some household assets (such as pension savings) are typically
not liquid enough to sustain the level of consumption of highly indebted households in a housing
34
downturn. This also points to the importance of the distribution of assets and debt among
households; in many countries, aggregate statistics mask large underlying variety in terms of
distribution. This implies that some groups of households own the assets, whereas debt has been
35
accumulated in other groups. The horizontal risk identification uses the following commonly used
indicators to analyse household stretch: households’ debt-to-income (DTI) ratios, household
leverage and households’ debt service ratios. Household stretch is related to collateral stretch
because higher RRE prices typically force households to take on additional debt to be able to
finance a house purchase and because RRE price increases lead to higher perceived wealth,
36
inducing households to borrow and consume more (see Chart 1.3). Additional indicators are used
in the vertical country-specific analysis (see Section 2.2), including the average DSTI ratio, the
37
average DTI ratio and the share of mortgages with variable interest rates.

30

See, for instance, Glick, R. and Lansing, K., “Global household leverage, house prices, and consumption”, FRBSF
Economic Letter, Federal Reserve Bank of San Francisco, 2010; Jordà, O., Schularick, M. and Taylor, A., “The Great
Mortgaging: Housing Finance, Crises, and Business Cycles”, Federal Reserve Bank of San Francisco Working Paper
No 2014-23, 2014; “Dealing with household debt”, World Economic Outlook: Growth Resuming, Dangers Remain,
International Monetary Fund, April 2012; and Mian and Sufi (2014) as above fn. 15.

31

Jordà, Schularick and Taylor (2014) ibid. See also Bank of England (2015) as above fn. 20.

32

Drehmann, M. and Juselius, M., “Do debt service costs affect macroeconomic and financial stability?”, BIS Quarterly
Review, September 2012. To the extent that household debt is denominated in foreign currencies or based on variable
interest rates, additional challenges emerge. See, for instance, the Recommendation of the European Systemic Risk
Board of 21 September 2011 on lending in foreign currencies (ESRB/2011/1).

33

Himmelberg, Mayer and Sinai (2005), as above fn. 27.

34

In addition, households may not be willing to draw down on their savings to sustain consumption.

35

Data on distributions are often lacking, which makes a comprehensive assessment of the role of household stretch more
difficult. This is also a limitation of the horizontal method in Section 2.

36

Turk (2015) as above fn. 23.

37

Some of these variables are included in Annex C.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Addressing vulnerabilities in residential real estate: a key task for macroprudential policymakers

19

Chart 1.3
Interactions between house prices and household indebtedness
(x-axis: change in HPI (2007-2014), percentages; y-axis: change in HH debt-to-income ratio (2007-2014), percentage points)

30
BE

SK

NL

20

CA

NO
SE

10

FI

IT

AU

FR
CL

SI
0

AT

PT

JP
HU

-10

DE

DK
EE

-20
IE
-30

UK

ES
US

LV

-40
-50

-40

-30

-20

-10

0

10

20

30

40

50

60

Sources: OECD and ESRB calculations.

Banking stretch – the ability of lenders to withstand losses when risks manifest: lower
collateral values resulting from RRE price drops and worsened economic conditions are associated
with increasing credit risk. Indeed, following periods of strong credit growth, the risks of economic
instability and financial crises are elevated. If credit risk manifests itself, lenders may not just suffer
reduced profitability or face capital losses, they may also face higher funding costs or even face
38
difficulties in obtaining sufficient funding. Vulnerabilities can also be aggravated by potential
exposure concentration in terms of the relative importance of mortgage lending in the balance
sheet of lenders. Concentration in the mortgage market itself is another source of vulnerability,
since it makes the market highly dependent on a few key suppliers of credit. Indicators to analyse
banking stretch include bank leverage, credit for house purchase (growth, as a proportion of GDP,
as a proportion of banks’ CET1 capital), average risk weights on mortgages and the share of short39
term funding (% of total funding).

38

ESRB 2015.

39

See Table 2.3 of Section 2.1.1.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Addressing vulnerabilities in residential real estate: a key task for macroprudential policymakers

20

Section 2
Analysing vulnerabilities in residential real estate 40
In this report, the analysis of residential real estate vulnerabilities rests on two pillars: (1) a
“horizontal” cross-country risk identification covering all 28 EU Member States; and (2) a “vertical”
country-specific analysis of risks and policies in eleven focus countries, organised around the
collateral, household and banking stretches.
In Section 2.1, the horizontal risk identification and analysis is presented. This is the method that
was used to identify the focus countries. The horizontal analysis is conducted in three steps (see
Box 1 for an overview of the horizontal analysis methodology and Annex B for more details):
1.

Horizontal analysis based on various key indicators and a creation of composite vulnerability
41
scores based on selected indicators (developed in cooperation with the ECB).

2.

An analysis of risks focusing on household, collateral and banking stretches.

3.

An analysis of structural and institutional factors that could potentially mitigate or aggravate
the risks identified. This analysis is subsequently used in the vertical analysis (see below).

In Section 2.2, the results of the “vertical” analysis for the focus countries are presented. The
assessments were conducted by the dedicated teams within the task force that were responsible
for the country analysis (the Country Teams), with significant input from authorities in the focus
42
countries and the ESRB Assessment Team on Macroprudential Measures. The vertical analysis
also benefited from information from third-party assessments, in particular those from the European
43
Commission, IMF and OECD.

40

The current horizontal framework for analysing RRE vulnerabilities, presented in Section 2.1, was developed jointly by the
ECB (the Directorate General Macroprudential Policy and Financial Stability – DG/MF) and the ESRB. The framework
builds on earlier ECB (DG/MF) and ESRB approaches to RRE analysis. The ESRB in particular thanks the colleagues from
the ECB, Federica Ciocchetta, Marco Lo Duca, Benjamin Klaus and Giulio Nicoletti, for their contribution.

41

For a description of the methodology, including an outline and justification of the indicators and thresholds in the horizontal
assessment, see Annex B. The methodology is identical to the one used by the ECB for euro area countries.

42

For a description of the methodology of the vertical assessment, see Section 2.2.1. See Annex A for an overview of the
teams in the RRE task force including their mandates and main forms of interaction.

43

Annex D contains an overview of third-party assessments for the focus countries.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Analysing vulnerabilities in residential real estate39F

21

2.1

Horizontal analysis of residential real estate vulnerabilities in EU
44
countries

Box 1
Methodology – horizontal framework for analysing RRE vulnerabilities
The current horizontal framework for analysing RRE vulnerabilities was developed jointly by the
ECB (DG/MF) and the ESRB. The framework builds on earlier ECB (DG/MF) and ESRB
approaches to RRE analysis.
The analytical framework consists of three steps: (1) a preliminary screening of vulnerabilities in
RRE markets (looking at, for example, RRE prices, lending conditions and household balance
sheets) focusing on the detection of “exuberant” developments; (2) an analysis of the strength of
the expansion in RRE markets; and (3) an analysis of banking sector resilience and potential
aggravating/mitigating institutional and structural factors.
In the first step, vulnerable RRE markets are identified on the basis of indicators covering RRE
prices, lending conditions and household balance sheets. The indicators used in this first step are
summarised in a scoreboard table which consists of a heat map with relevant risk thresholds and
summary indicators to facilitate country rankings (Table E.1). The indicators in the scoreboard
capture three risk categories and are explained in detail in Table B.1. Specifically, the categories
are:
•

collateral stretch: indicators capture potentially “exuberant developments in RRE markets” which
relate also to stretched collateral values (and can feed into lending conditions);

•

lending conditions: indicators capture potentially “exuberant developments in lending conditions”
which can relate to underpricing of risk and might also feed into RRE price developments;

•

household stretch: indicators capture household vulnerabilities which relate to potential credit risk
and its dynamics.
The scoreboard thresholds are guided by model evidence, where possible, and by the distribution
of the indicators; the plausibility is checked on the basis of expert judgement. Explanations and
data sources for each indicator are provided in Table B.1. The dates of the observations underlying
the scoreboard are also reported in Table B.2.
Two composite indicators, summarising the level of vulnerabilities in a country, are used to facilitate
an initial country ranking.

•

The average rating across indicators (the penultimate column of the scoreboard) is an equally
weighted average of a discrete transformation of the individual indicators. Each indicator is
assigned a rating from 0 to 3 on the basis of the threshold it breaches (0 = no threshold breached, 3
= highest threshold breached indicating high risk). The summary indicator is simply the average of
the ratings of individual indicators. The first threshold of the composite indicator is set at 1 (i.e.
individual indicators breaking the first risk threshold on average) and corresponds to a yellow

44

The current horizontal framework for analysing RRE vulnerabilities was developed jointly by the ECB (DG/MF) and the
ESRB. The framework builds on earlier ECB (DG/MF) and ESRB approaches to RRE analysis. The horizontal analysis has
been developed by colleagues from the ECB (Federica Ciocchetta, Marco Lo Duca, Benjamin Klaus and Giulio Nicoletti)
and adapted for the use of the ESRB.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Analysing vulnerabilities in residential real estate39F

22

colouring. The second (orange colour) and third (red colour) threshold are set on the basis of the
80th percentile and 90th percentile of the distribution of the indicator across countries and over
time.
•

The composite indicator (the last column of the scoreboard) reports the average distance (in terms
of standard deviation) of indicators from the lowest thresholds. It is calculated as an equally
weighted average of the standardised indicators. Standardisation is achieved by deducting the
lowest threshold from each indicator and dividing by the standard deviation of the indicator
(calculated across countries and over time). The first threshold of the composite indicator is set at 0
(i.e. individual indicators breaching the first risk threshold on average) and corresponds to a yellow
colouring. The second (orange colour) and third (red colour) threshold are set on the basis of the
80th percentile and 90th percentile of the distribution of the indicator across countries and over
time.
As the resulting ranking of countries according to summary indicators critically depends on the
thresholds, the set of indicators used and the weighting scheme used for the aggregation, a
number of robustness checks are performed. These have yielded similar results.
The second step of the analysis consists in determining the position of a country in the housing
cycle as suggested by the household income and collateral stretches by looking at indicators
capturing the “strength” of the expansion across countries.
Finally, in a third step, the analysis of the household income and collateral stretches is
complemented by an analysis of risks coming from the banking sector stretch (exposures of the
banking system to risks and the consequent analysis of resilience).
In addition, the vulnerable RRE markets are analysed on the basis of institutional and structural
factors that might act as amplification or mitigation mechanisms for shocks, as detailed in Section
2.1.2.

2.1.1

Horizontal analysis: indicator-based analytical framework

The indicator-based analytical framework suggests a diversity of vulnerabilities across the
EU countries. An overview of the signals provided by the analytical framework (see Box 1 for a
45
description of the methodology) developed by the ECB/ESRB is provided in Table 2.1. As
illustrated in this table, there is a large diversity in terms of the indicators that drive the composite
vulnerability measures at the country level. On the one hand, there are many countries which
display few signals of vulnerabilities in RRE. On the other hand, there are a number of countries
where the framework signals vulnerabilities. This group includes countries which recently
experienced a RRE-related crisis and still suffer from related legacy issues, and countries where a
materialisation of (further) RRE-related risk may occur over the medium term. In the remainder of
this report, the analysis focuses on the latter group.

45

For a description of the methodology, including an outline and justification of the indicators and thresholds used in this
analysis, see Annex B.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Analysing vulnerabilities in residential real estate39F

23

Table 2.1
Vulnerabilities in RRE across the EU: results from the indicator-based horizontal analysis
Indicators
Collateral Stretch

Country

Residential real
estate
price
index,
12m
growth,
%

ResidenRRE
tial price valuation
index
measure,
relative to
house
peak prior price to
to 2014
income

AT

8.1

1.1

26.0

BE

2.3

1.0
0.8

BG
CY

-1.6

CZ

Summary measures

Lending Indicators
Loans to Loans to
HH for
HH for
RRE
house
HP
valuation
purrelative
measure,
chases,
to peak
econome12m
prior to
tric model growth, %
2014

Household Stretch

HH
Loan
spread

HH
debt,
% of
GDP

HH
finanDebt
cial
service Average
assets
to
rating
to
income across
debt, ratio for indica%
HH, %
tors

Composite
indicator

14.0

4.9

1.1

2.1

51.2

350.8

10.2

1.4

0.3

26.0

4.0

8.1

1.2

1.8

59.6

500.2

10.7

1.5

0.2

-9.0

-11.0

0.6

1.0

5.6

23.8

552.6

8.1

0.0

-0.9

0.7

-16.0

-3.0

-1.8

0.9

3.2

127.3

206.0

28.8

0.9

0.3

1.0

8.0

2.0

8.7

1.1

30.3

360.4

8.2

0.8

-0.1
0.1

DE

4.7

1.1

4.7

-2.0

3.7

1.1

1.9

53.4

338.1

9.4

0.8

DK

3.5

0.9

19.0

4.0

1.2

1.0

1.4

122.8

248.5

20.4

1.5

0.6

EE

0.8

0.9

8.0

-7.0

4.6

1.0

2.3

40.6

270.4

7.6

0.4

-0.2

ES

6.3

0.7

-6.0

5.0

-3.5

0.8

1.9

66.4

275.8

12.9

0.5

-0.1

FI

-0.1

1.0

10.0

3.0

2.6

1.0

1.4

66.7

210.9

11.4

1.4

0.2

FR

0.3

0.9

14.0

4.0

3.2

1.0

1.7

56.5

394.1

10.0

1.0

0.0

GR

-5.0

0.6

-25.0

-5.0

-3.6

0.8

2.7

61.8

218.3

21.8

0.7

-0.2

HR

-2.1

0.8

-11.0

-16.0

-4.8

0.8

4.4

36.9

302.7

8.8

0.0

-0.6

HU

4.3

0.9

-7.0

-15.0

-3.3

0.6

4.6

21.2

563.5

7.6

0.1

-0.9

IE

7.4

0.7

-3.0

-23.0

-4.2

0.6

3.4

57.8

237.3

19.9

0.7

-0.4

IT

-1.2

0.8

-5.0

0.9

1.0

1.6

42.1

581.5

11.8

0.3

-0.3

LT

10.5

0.7

-3.0

-8.0

6.6

1.0

1.9

22.3

414.2

5.1

0.6

-0.4

LU

4.5

1.1

18.0

9.0

7.0

1.2

1.7

57.4

242.1

10.8

1.8

0.4

LV

7.4

0.7

-6.0

-19.0

-2.2

0.7

3.3

24.3

430.8

5.7

0.2

-0.8

MT

10.0

1.1

10.0

-9.0

7.9

1.2

2.3

57.8

462.8

12.8

1.6

0.1

NL

4.4

0.9

-4.0

2.0

6.2

1.1

2.8

111.4

296.7

21.5

0.9

0.3

PL

1.8

0.9

-9.0

-17.0

0.7

1.1

1.4

36.2

268.6

13.4

0.5

-0.2

PT

5.0

0.9

-9.0

-3.0

-3.5

0.8

2.0

76.3

269.5

16.4

0.6

0.0

RO

3.6

0.7

-20.0

-29.0

16.5

1.3

2.8

17.2

414.6

6.5

0.6

-0.6

SE

12.9

1.3

69.0

47.0

8.7

1.1

84.7

333.4

16.0

2.2

1.2

SI

0.8

0.8

-10.0

-8.0

3.2

1.0

2.0

27.5

367.4

5.8

0.1

-0.4

SK

1.0

0.8

-6.0

-15.0

13.8

1.3

2.3

35.8

213.9

10.0

1.0

-0.1

UK

8.7

1.0

30.0

11.0

4.6

1.1

87.0

372.9

18.4

1.7

0.6

EAA

2.4

1.0

4.7

-1.0

2.1

1.0

59.3

356.1

0.5

0.0

EAM

4.5

0.9

-3.0

-3.0

3.2

1.0

57.4

296.7

0.8

0.0

EUA

2.0

10.8

1.0

1.0

0.4

EUM

4.4

0.9

-3.0

-3.0

3.2

1.0

2.1

54.9

335.8

10.8

0.7

-0.1

T1

4.0

0.9

2.5

2.5

5.0

1.0

1.5

50.0

220.0

10.0

1.0

0.0

T2

6.5

1.0

5.0

5.0

7.5

1.1

1.8

70.0

240.0

15.0

1.2

0.2

T3

9.0

1.1

7.5

7.5

10.0

1.2

2.0

90.0

260.0

20.0

1.7

0.5

TR

4.0

0.9

2.5

2.5

5.0

1.0

2.0

50.0

260.0

10.0

Sources: ESRB and ECB (see Annex B for specific sources and detailed definitions of the indicators).
Notes: EAA is the euro area average; EAM is the euro area median; EUA is the EU average; EUM is the EU median; T1, T2, T3 and TR are risk
thresholds. See Box 1 and Annex B for a description of the methodology underlying these results. In Finland, the household financial assets-to-debt
indicator excludes earnings-related pension assets. Including assets held by the Finnish employment pension schemes, the ratio would be around
337%.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Analysing vulnerabilities in residential real estate

24

A set of key indicators suggest that vulnerabilities in the collateral and household stretches
are elevated in Austria, Belgium, Denmark, Estonia, Finland, Luxembourg, Malta, the
46
Netherlands, Sweden, Slovakia and the United Kingdom. Several of these countries have
high household indebtedness; however, Austria, Estonia and Slovakia all have a household debtto-GDP ratio below the EU median. In Denmark and the Netherlands, this is particularly
pronounced, with household debt reaching 122.8% and 111.4% of GDP, respectively. Household
debt dynamics also suggest increasing vulnerabilities in many countries. In Slovakia, Belgium,
Malta and Sweden, household debt as a share of GDP rose rapidly last year. The cumulative
increase since 2011 is also significant in Denmark, Malta, the UK, Sweden and Luxembourg (see
Chart 2.1). For all countries with high household debt levels, debt service ratios also appear
elevated, despite the low interest rate environment. Low loan spreads could indicate underpricing of
risks and exuberant lending policies, but the low spreads could also be due to a competitive lending
market. Finland, Denmark and Luxembourg are in particular characterised by low loan spreads.
Along the dimension of collateral stretch, price-to-income (PTI) ratios have increased in many
countries, particularly in Austria and Sweden where the PTI ratio in the first quarter of 2016 was,
47
respectively, 27% and 22% higher than in 2010. It is difficult to measure overvaluation and
undervaluation in RRE markets, since the results depend on the underlying assumptions but,
compared with income, RRE prices might be overvalued in Sweden, Austria, Belgium and the UK –
48
in these countries, prices are also at historical peak levels (see Chart 2.1).
Dynamics of the indicators suggest that vulnerabilities are increasing in a number of the
above-mentioned countries (see Chart 2.1). Growth in RRE prices over the last 12 months
characterises all the countries mentioned above, with the exception of Finland where RRE prices
49
have remained stable. In a number of countries, RRE price growth has been particularly strong in
recent years. This also applies to price developments in the past year: Belgium (+7%), Austria
(+8%), the UK (+9%), Malta (+10%) and Sweden (+13%). A recurrent pattern relates to the
concentration of the RRE price increase and overvaluation in major cities across Europe compared
with non-urban areas. For instance, in the last three years, RRE prices in London have been
growing on average by 12% (vs. 7.5% for the UK), and in Amsterdam by 7.5% (whereas growth in
50
RRE prices in the Netherlands as a whole has remained subdued in the last three years). In
addition, the growth rates in loans for house purchase are high in Slovakia (13.8%), Sweden
(8.7%), Belgium (8.1%), Malta (7.9%), Luxembourg (7.0%) and the Netherlands (6.2%). Moreover,
trends in lending for house purchases are strongly interlinked with RRE price dynamics, particularly
in some countries.

46

The list of countries does not completely correspond to the countries highlighted in Table 2.1 and Chart 2.1. This relates to
the fact that the initial identification of countries was based on an earlier methodology and older data.

47

For Malta, the analysis in the scoreboard (Table 2.1) has been replicated with Malta’s official index for residential real
estate prices based on transacted property prices (Eurostat series teicp270). The results show that: (i) 12-month growth in
the RRE price index is 1.0%; (ii) the residential price index relative to the peak prior to 2014 is 1.03 and is marked in
orange; and (iii) the average rating across indicators is 1.2 and is marked in orange. These results confirm the assessment
of Malta.

48

Figures refer to PTI ratio levels (index: 2010 = 100) and overvaluation. For a detailed description of the methodology to
calculate RRE price overvaluation, see Box 3 in ECB 2015c.

49

See footnote 47.

50

“Hot in the City”, The Economist, 2 April 2016.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Analysing vulnerabilities in residential real estate39F

25

Chart 2.1
Developments in collateral and household stretch
a) Developments in the collateral stretch

b) Developments in the household stretch

(x-axis: RRE annual price growth;
y-axis: RRE valuation;
bubble size: weighted by percentage change in RRE prices since Q1
2011 (empty bubbles indicate negative developments))

(x-axis: loans to households for house purchase, annual growth in %;
y-axis: household debt-to-GDP ratio, %;
bubble size: weighted by change in household debt-to-GDP ratio since
Q1 2011 (empty bubbles indicate negative developments))

60

140
CY

50

SE

DK

120

40

NL
100

30

UK

20

80

AT
ES UK

10

-20

FR LU
FI CZ DK BE
CY
NL PT
IT
DE
EE
SI
BG
PL
SK
LV
HR

-30

RO

0
GR
-10
HU

60

MT

IE

ES
GR

LT

FI

HR

PL

HU

20

LV

BE

FR
DE

IT

40

IE

SE

PT

BG

AT LU MT
EE
CZ
SI

SK

LT

RO

0

-40
-15

-10

-5

0

5

10

15

-10

-5

0

5

10

15

20

Sources: ECB and ECB/ESRB Secretariat calculations.

The economic outlook sheds light on potential future developments in RRE vulnerabilities.
The price dynamics together with the overall economic outlook for the focus countries (see Table
2.2) may also shed light on potential future vulnerabilities related to residential real estate. Strong
economic growth rates and outlooks in Malta, Slovakia and Luxembourg (and to a lesser extent
Estonia and Sweden) signal that vulnerabilities related to RRE are likely to continue to rise, unless
their current macroprudential policy stances are effective in curbing further build-up. By contrast, in
Finland and – to a lesser extent – Austria, Belgium and Denmark, the subdued economic outlook
increases the probability of the materialisation of a reinforcing spiral of adverse dynamics in the
housing market and the real economy. The outlook for the UK is surrounded by uncertainty
following the UK’s referendum on EU membership on 23 June 2016.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Analysing vulnerabilities in residential real estate39F

26

Table 2.2
Economic outlook in EU countries
Real GDP

2015

2016

2017

Real GDP

2015

2016

2017

BE

1.4

1.2

1.6

AT

0.9

1.5

1.6

DE

1.7

1.6

1.6

PT

1.5

1.5

1.7

EE

1.1

1.9

2.4

SI

2.9

1.7

2.3

IE

7.8

4.9

3.7

SK

3.6

3.2

3.3

GR

-0.2

-0.3

2.7

FI

0.5

0.7

0.7

ES

3.2

2.6

2.5

BG

3.0

2.0

2.4

FR

1.2

1.3

1.7

CZ

4.2

2.1

2.6

IT

0.8

1.1

1.3

DK

1.2

1.2

1.9

CY

1.6

1.7

2.0

HR

1.6

1.8

2.1

LV

2.7

2.8

3.1

HU

2.9

2.5

2.8

LT

1.6

2.8

3.1

PL

3.6

3.7

3.6

LU

4.8

3.3

3.9

RO

3.8

4.2

3.7

MT

6.3

4.1

3.5

SE

4.1

3.4

2.9

NL

2.0

1.7

2.0

UK

2.3

1.8

1.9

Source: European Commission spring 2016 forecast.
Notes: Following the outcome of the UK’s referendum on EU membership in June 2016, the economic outlook has changed. The forecasts in this
table predate the referendum. The Bank of England projects that UK GDP will grow by 0.8% in 2017; the estimate was revised down from 2.3% after
the referendum. 51

There are some signs of banking stretch related to real estate in Austria, Finland, Belgium,
Denmark, the Netherlands, Sweden and the United Kingdom (see Table 2.3). The mortgage
52
stock in relation to capital exceeds 600% in Denmark , the Netherlands and Sweden. In these
countries, this corresponds closely to the gross domestic product. Low risk weights (Luxembourg,
Finland, Belgium and the UK) imply less resilience of banks to manifestations of credit risk.
Moreover, bank leverage is relatively high in Finland (19), Sweden (19), the Netherlands (18),
Denmark (17) and the UK (16). At the other end of the spectrum lies Estonia with a leverage ratio of
around 8, also reflected in a very high CET1 ratio (35%). Mortgages are also high in relation to
capital in Finland and Belgium (421% and 413% respectively). In Estonia, Finland, Austria and
Malta, the domestic banks also have significant exposures to non-financial companies engaged in
real estate activities. In Austria, this is also accompanied by one of the lowest CET1 levels in the
EU. For some countries, the proportion of market funding is considerable, which adds to banking
stretch. This is particularly the case in Denmark (50% of total funding) and Sweden (52% of total
funding). Large proportions of short-term wholesale funding also confirm the banking stretch
indicated in Luxembourg (89%).

51

Inflation Report, Bank of England, August 2016.

52

The ratio for Denmark is significantly lower if mortgage credit institutions are included.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Analysing vulnerabilities in residential real estate39F

27

Table 2.3
Banking stretch related to residential real estate: key indicators
Indicators

Risk Weights
on Residential
Real Estate
(IRB banks)

Total mortgage
Total mortgage
loans
loans
outstanding, as
outstanding, as
% of CET1,
% of GDP, BSI
CBD (1)

Short-term
market funding
to total market
funding (%),
ANBS report

Proportion of
Market
Funding %,
ANBS report

CET1 capital
ratio, %, CBD

Leverage ratio,
%, CBD (2)

AT

24.00

27.96

165.26

54.90

19.66

12.65

13.53

BE

10.00

31.44

413.79

74.10

10.84

15.43

14.74

78.10

0.65

19.47

7.68
10.73

BG

9.89

CY

65.96

236.15

89.10

1.03

15.61

CZ

21.55

221.96

65.40

6.79

15.85

9.75

58.00

19.43

14.90

18.56

49.7 (5)

16.17

16.67

DE

16.00

35.59

87.27

DK

14.00

106.70

641.34 (4)

EE

15.00

30.78

183.60

83.90

0.16

34.79

7.73

ES

15.00

50.20

440.85

58.40

13.57

12.66

13.72

FI

<10.00

43.80

421.38

66.60

17.83

21.41

19.06

FR

15.00

40.56

194.26

70.70

19.80

12.57

17.26

GR

37.77

195.69

84.90

2.06

16.31

10.95

HR

15.97

102.30

83.10

0.25

17.71

7.96

HU

8.68

67.50

5.28

13.23

11.31

IE

37.00

35.87

241.74

74.40

16.90

22.30

7.82

IT

18.00

21.99

252.96

55.80

19.68

11.80

13.13

16.69

274.56

58.50

0.24

24.29

9.04
13.45

LT
LU

47.05

50.98

89.20

9.58

20.11

LV

18.21

138.59

84.20

2.53

18.98

9.52

MT

44.15

154.13

78.60

1.10

18.02

14.07

62.36

638.97

50.00

28.45

14.65

17.95

20.66

244.97

56.40

4.62

14.50

9.18

22.00

53.62

383.89

49.00

8.93

12.42

12.37

7.31

215.33

87.10

0.81

16.38

9.79

25.00

65.75

641.27

49.00

52.47

18.92

18.82
8.57

NL

10.00

(3)

15.00

PL
PT
RO
SE
SI

14.26

93.57

64.00

3.64

17.98

SK

25.64

391.99

51.50

7.32

16.02

8.99

69.20

18.16

13.76

15.63

UK

11.00

55.28

Sources: ECB balance sheet item (BSI) statistics, ECB consolidated banking data (CBD), November 2015 Analysis of the national banking systems
(ANBS) report, EBA 2015 Transparency Exercise and national authorities.
Notes:
(1) The total mortgage loans series uses consolidated banking data and therefore captures cross-border lending. However, it is necessary to use this
data for consistency with the denominator, CET1 capital.
(2) Leverage ratio defined as total assets/total equity.
(3) Risk weights in Luxembourg are reported for all banking sectors for consistency purposes. Note that the (seven) banks active in real estate
lending have higher risk weights (16%).
(4) The ratio for Denmark is significantly lower if mortgage credit institutions are included.
(5) Regulation does not permit specialised mortgage banks in Denmark to take deposits; they must instead fund their lending through the issuance of
covered bonds.

2.1.2

Horizontal analysis: structural and institutional features

Structural and institutional features and developments in recent years vary considerably
across the EU. RRE markets in the EU display considerable diversity in terms of structural and
institutional features. It is difficult to provide a clear view of how these features affect probabilities
and potential impacts of RRE-related crises, especially since such features interact and often have

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Analysing vulnerabilities in residential real estate39F

28

53

both amplifying and mitigating effects that vary over the financial cycle. However, developments
in recent years show that even within groups of countries with similar structural characteristics,
54
some countries were hit by RRE-related crises, whereas others were not.
National RRE markets are products of geographical, socio-economic, political and other
factors. While geographical, demographic and cultural factors are key determinants of countryspecific structural and institutional features, some features are also the result of conscious or
unconscious political design. Housing is indeed one of the most regulated sectors, where a vast
array of regulatory objectives interact to produce distinct national characteristics. This includes not
only the availability and affordability of housing itself, but also (redistributive) tax policy, health and
55
safety regulation, environmental regulation and spatial planning. Needless to say, geographical
conditions, including infrastructure, also display considerable variation across countries.
RRE vulnerabilities should be considered in the light of national specificities. Comparing
structural and institutional features in the RRE markets across the EU reveals cross-country
similarities, but also considerable differences (see Table 2.4). The paragraphs below use the
information on structural and institutional features presented in Table 2.4 to analyse how the main
structural and institutional features affect the vulnerabilities in the countries identified in the
indicator-based analysis (see Section 2.1.1). However, analysing the way in which such structural
and institutional features amplify or mitigate RRE-related vulnerabilities is extremely complex – not
least since the effects may depend on interactions with other policies, and in particular on whether
56
vulnerabilities are rising or already elevated. One should also bear in mind that structural features
and their expected developments tend to be priced in to housing market expectations and
equilibria. This implies that unexpected structural changes (e.g. a comprehensive tax reform,
reversed migration flows, etc.) may have large implications for RRE vulnerabilities.
High home ownership and rental market restrictions potentially amplify and interact with
RRE-related vulnerabilities. Academic research has identified home ownership and rental market
characteristics as factors having a bearing on real estate-related vulnerabilities. The evidence from
the global financial crisis shows that EU countries with higher home-ownership rates not only
experienced larger RRE price increases in the run-up to the crisis, but also saw sharper RRE price
57
corrections in the crisis. High home-ownership rates have also been found to have a strong
58
positive effect on RRE price volatility in a global context and over time. This could suggest that
high home-ownership rates potentially amplify and interact with other RRE-related vulnerabilities, in

53

Wheaton, W., “Real estate ‘cycles’: some fundamentals”, Real Estate Economics, Vol. 27(2), 1999, pp. 209-230; Malpezzi,
S. and Wachter, S., “The role of speculation in real estate cycles”, Journal of Real Estate Literature, Vol. 13(2), 2005, pp.
143-164.

54

See ESRB 2015 for further details on the structural and institutional features of national RRE markets, including a
discussion on how such features may amplify or mitigate systemic risks.

55

For a comprehensive discussion of these matters, see Andrews, D., Caldera Sanchez, A. and Johansson, A., “Housing
markets and structural policies in OECD countries”, OECD Economics Department Working Paper No 836, 2011; and
“House price imbalances and structural features of housing markets”, Quarterly Report on the Euro Area, Vol. 10,
Issue 3, European Commission, October 2011.

56

It is difficult to assess the precise impact of these parameters, as it typically depends on the combination of structural
characteristics in place (ECB 2015a). It should also be noted that the structural and institutional features of national RRE
markets are to some extent captured in the risk weights applied by IRB banks, in cases where these features impact on the
probability of default and loss given default of mortgage exposures.

57

ESRB 2015.

58

Kappler, M., Kröncke, T.-A., Schindler, F., Schleer, F., Seymen, A. and Westerheide, P., “Housing Markets and Intra-Euro
Area Macroeconomic Imbalances: Identifying Policy Instruments”, European Commission – Directorate General for
Economic and Financial Affairs (DG ECFIN), 2011; and ESRB 2015.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Analysing vulnerabilities in residential real estate39F

29

both the upturn and downturn of the housing cycle. In the former, they may cause a mutually
reinforcing spiral of increasing RRE prices, credit and household indebtedness. In the latter, large
price drops could aggravate the effects of negative feedback loops between falling RRE prices,
reduced household consumption and losses and credit contractions among banks. Of the focus
countries, Slovakia and Estonia have home-ownership rates that are significantly above the EU
average. The opposite holds for Austria and Denmark, where the market is more balanced between
owner-occupied and rented dwellings. Some countries (such as Denmark and Sweden) have
strongly regulated rental markets; in some cases this coincides with underdeveloped rental
markets. While specific research is lacking on the implications of restrictions on rental markets,
underdeveloped rental markets should intuitively lead to similar amplifying effects to those seen for
59
high home ownership.
60

Vulnerabilities can be amplified by tax breaks and subsidies. A key feature of many national
tax systems is direct and indirect housing subsidies – the latter typically in the form of mortgage
interest deductibility. Tax deductibility reduces the net cost for households of servicing their debt,
and gives households the possibility and the incentive to borrow more. Experience indicates a
moderate effect of tax deductibility on RRE price volatility, possibly by increasing post-tax returns
on (speculative) housing investment. Also, it tends to encourage indebtedness, which is in turn
61
related to higher RRE prices. A more comprehensive way to analyse the effects of taxes on
housing market dynamics is to observe the difference between the market rate and the financing
62
cost of housing. Such a tax burden has a strong effect on price volatility in RRE markets. When
the tax burden is high – due to high recurring property taxes or low subsidies/tax relief – RRE price
63
volatility tends to be lower and vice versa. Property tax measures can therefore have the effect of
automatic stabilisers on the housing market. At the same time, distortionary effects from property
64
taxes are usually smaller than from other taxes, e.g. taxes on labour or capital income. The
marginal contribution of tax to the cost of housing data shows that the focus countries generally
have lower tax burdens on housing than the EU average (10.1 compared with 12.7). This is
particularly pronounced for Estonia and the Netherlands, where tax systems significantly reduce
households’ housing expenditure. This, in turn, may amplify vulnerabilities in residential real estate.
The opposite characterises Denmark, Belgium and the UK, where the marginal contribution of tax is
more than twice the EU average.
Transaction costs can discourage speculation, but also reduce liquidity. Transaction costs –
in the form of capital gains tax, stamp duties, legal fees, etc. – have also been found to have a

59

These findings do not take into account the indebtedness of households or differentiate between mortgaged and nonmortgaged households.

60

There are a number of features relating to tax and subsidies which are left out of this analysis, including social housing,
rental market taxation and outright subsidies (such as the government mortgage subsidy in Slovakia).

61

Harris, B., “The Effect of Proposed Tax Reforms on Metropolitan Housing Prices”, Tax Policy Center, Urban Institute
and Brookings Institution, April 2010; Andrews et al. (2011) as above fn. 55.

62

For a discussion of tax effects on housing, see Van Den Noord, P., “Tax incentives and house price volatility in the euro
area: Theory and evidence”, Économie Internationale, Vol. 101, 2005(1), pp. 29-45; ESRB 2015; ECB 2015a; and Andrews
et al. (2011) as above fn. 55.

63

ECB 2015a; Harris (2010) as above fn. 61; and European Commission (2011) as above fn. 55. Please note that “taxes” in
this paragraph refers to taxes, charges and fees that are recurring, and not taxes that relate to transactions or other one-off
charges and fees.

64

Ormaechea, S. A. and Yoo, J., “Tax Composition and Growth: A Broad Cross-Country Perspective”, IMF Working
Paper WP/12/257, 2012.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Analysing vulnerabilities in residential real estate39F

30

65

negative but small effect on RRE price volatility. This is probably due to disincentives for
speculative house purchases. The effect is somewhat counterbalanced by a reduction in the
number of houses offered for sale and the number of transactions, which may increase RRE price
volatility. While the magnitude of these effects may differ across countries (due to influences from
other policies and structural features), high transaction taxes – particularly in Belgium but also to a
lesser extent in Luxembourg – may mitigate vulnerabilities in RRE. However, the transaction cost
estimates in Table 2.4 exclude costs relating to stamp duties, legal and administrative fees, etc.,
which have the same directional effects as transaction costs, but for which comparable data are
unavailable.
Mortgage maturities vary significantly among countries. The focus countries are characterised
by relatively longer mortgage maturities than in other EU countries. Swedish housing loans, and to
a lesser extent those in the Netherlands and Denmark, particularly stand out in this respect. Long
maturities imply that amortisation, and thus the rate of reducing household indebtedness, are
expected to be low. Of course, other features – such as the interest rate fixation period and the type
of amortisation – can interact with the length of the maturity. Furthermore, mortgages with shorter
maturities can be repeatedly rolled over in some cases. Longer maturities imply that there is less
natural reduction in vulnerability levels related to household indebtedness. Related to this it is
noteworthy that in some countries full amortisation of mortgages is not required or common.
The EU is characterised by large cross-country variations in price elasticities of housing
supply. Housing supply strongly influences housing market dynamics, and is a complex function of
geographical conditions (such as the supply of zoned and serviced land, urbanisation, etc.) and
institutional factors (such as planning restrictions, building approval processes, etc.). Price elasticity
of supply has been identified as particularly important. While housing supply generally tends to be
relatively inelastic to price changes in the short run, the variation across countries is probably
66
greater over the long run. Also, elasticity is likely to be particularly low in urban areas, especially
in the absence of a well-developed infrastructure for commuting or given restricted availability of
land.
The responsiveness of housing supply to price changes has mixed effects on RRE
vulnerabilities. When the housing supply is elastic to price changes, as is the case in the Nordic
countries, real RRE price volatility tends to be lower. This may mitigate RRE vulnerabilities.
However, the mitigating effect may be countered by the risk of overshooting in the construction
67
sector. In turn, this may magnify a fall in RRE prices if demand subsequently weakens. This may
potentially characterise developments in Estonia, where recent investments in RRE in relation to
GDP have been significantly higher than the EU average. When the responsiveness of new
housing supply is low, which is the case in Austria, Belgium and the Netherlands, price effects from
demand shocks can be exacerbated. This, in turn, may increase volatility and the risk of

65

Andrews et al. (2011) as above fn. 55; ESRB 2015.

66

European Commission (2011) as above fn. 55; Bacon, P., MacCabe, F. and Murphy, A., “An Economic Assessment of
Recent House Price Developments”, Government of Ireland Publications, Stationery Office, 1998.

67

European Commission (2011) as above fn. 55; Caldera Sánchez, A. and Johansson, Å., “The Price Responsiveness of
Housing Supply in OECD Countries”, OECD Economics Department Working Paper No 837, 2011; Glaeser, E. L.,
Gyourko, J. and Saiz, A., “Housing supply and housing bubbles”, Journal of Urban Economics, Vol. 64(2), 2008, pp. 198217.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
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31

68

overvaluation, thereby amplifying RRE vulnerabilities. Indeed, evidence suggests that countries
69
with a low elasticity of housing supply display longer and more pronounced housing bubbles.
However, the risk of oversupply of housing through a construction boom is lower.
Population and household dynamics are key drivers of housing demand. In addition to
increases in income and trends towards (de)urbanisation, demographic developments and changes
70
in household structures are typically seen as key drivers of housing demand. For instance,
estimates show that population growth caused by population increases tends to translate into
71
higher real RRE prices. Large population increases, which in the past have characterised
Luxembourg and to a lesser extent Sweden and Austria, may therefore shield the housing market
from significant price drops, potentially mitigating vulnerabilities. However, large population
increases can also make the housing market vulnerable to subsequent population declines, such
as the one experienced in Ireland recently). Evidence also suggests that household structure in
72
combination with housing supply influences RRE price dynamics. Whereas the stock of dwellings
per capita is a common measure of housing supply, it also reflects cultural differences and displays
a high correlation with variables such as the share of single households. Changes in household
structures may therefore be more useful in explaining housing dynamics over time.

68

An analysis by the OECD (Andrews et al., 2011 as above fn. 55) suggests that in a country with supply responsiveness half
a standard deviation below the median OECD country, the increase in RRE prices linked to a demand shock is roughly
50% larger than if the responsiveness was at the median. Thus, in rigid supply environments, increases in housing demand
are much more likely to be capitalised into RRE prices than to spur increases in the quantity of housing, at least over the
medium-term horizon covered by the OECD analysis. See also Caldera Sánchez and Johansson (2011) as above fn. 67.

69

Glaeser, Gyourko and Saiz (2008); Glaeser, E., Gyourko, J. and Saks, R. E., “Why have house prices gone up?”, American
Economic Review, Papers and Proceedings, Vol. 95(2), May 2005, pp. 329-333; Grimes, A. and Aitken, A., “Housing
supply, land costs and price adjustment”, Real Estate Economics, Vol. 38(2), 2010, pp. 325-353; Paciorek, A., “Supply
constraints and housing market dynamics”, Journal of Urban Economics, Vol. 77(C), 2013, pp. 11-26.

70

Many of the indicators in the composite vulnerability analysis are adjusted for income (price-to-income, debt-to-income and
debt service ratios).

71

See for instance Conefrey, T. and Fitzgerald, J., “Managing housing bubbles in regional economies under EMU: Ireland
and Spain”, National Institute Economic Review 211, 2010; Cvijanovic, D., Favilukis, J. and Polk, C., “New in Town:
Demographics, Immigration, and the Price of Real Estate”, London School of Economics and Political Science, 2010;
Structural factors in the EU housing markets, ECB, 2003.

72

Changes in family structure contributed to housing boom/bust cycles in Ireland, Spain and the UK as discussed in Duca, J.,
Muellbauer, J. and Murphy, A., “Housing Markets and the Financial Crisis of 2007-2009: Lessons for the Future”, Journal of
Financial Stability, Vol. 6(4), December 2010, pp. 203-217.

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Vulnerabilities in the EU residential real estate sector November 2016
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32

Table 2.4
Structural and institutional features of RRE markets in all EU countries
Market characteristics

Dwellings
per capita
AT
BE

0.35

Home
ownership

Prevailing type of
interest rate

57.3

Variable

72.3

Long term fixed

BG

85.7

CY

74.0

CZ

80.1

Short term fixed
Medium term fixed

DE

0.32

52.6

DK

0.42

63.0

EE

Tax & transaction
Contribution
of tax to
marginal
cost of
housing

Supply-side characteristics

Transacti
on tax

Estimated
longrun price
elasticity of
new housing
supply

RRE
investment/G
DP (annual
average
1995-2014)

Demand-side characteristics

RRE
Investments/
GDP (annual
change in
2013)

Construction
cost index

Change in
single
households
(%)
2004-2014

Typical
mortgage
maturities
(years)

Mortgage Tax Relief
None

6.9

< 5%

0.2

4.9

1.8

85.2

5.7

16.6

2.1

21.4

Bounded

24.0

≥ 10%

0.3

5.7

-1.4

95.5

2.5

15.0

1.2

20.0

Bounded and Limited

-0.3

2.8

2.3

88.6

-0.2

9.2

-26.3

99.7

-13.9

7.6

-4.3

83.6

0.4

11.6

None
Bounded and Limited

0.2
1.6

< 5%

7.9

Net migration Single
(per 1000
households
inhab.)
(%)

30.0

None

9.8

5-9%

0.4

3.4

2.7

91.9

5.3

20.2

27.2

Bounded

20.0

< 5%

1.2

6.0

-4.4

94.9

3.0

22.7

Bounded and Limited

-5.3

4.6

17.0

87.9

-2.0

9.8

81.1

Variable

22.6

1.2

ES

0.37

77.7

Variable

22.7

None

24.1

5-9%

0.5

3.6

-15.7

91.3

-5.4

FI

0.41

73.6

Variable

21.6

Bounded

7.5

< 5%

1.0

7.4

-1.4

90.5

3.3

19.9

2.2

FR

0.39

64.3

Long term fixed

18.6

None

32.5

5-9%

0.4

8.0

-2.2

83.3

0.5

16.2

1.9

GR

0.42

75.8

Variable

None

30.2

< 5%

5.7

-33.3

88.7

-5.4

10.2

2.8

5-9%

5.8

89.2

-1.1

8.8
8.8

HR

88.5

HU

None

89.6

Variable

15.0

None

11.0

< 5%

3.6

-30.3

88.5

0.4

IE

0.22

69.9

Variable

26.4

None

15.8

< 5%

0.6

7.1

8.4

97.2

-5.3

IT

0.42

73.0

Variable

21.9

Bounded and Limited

22.1

5-9%

0.3

5.1

-4.8

87.0

3.0

14.1

92.2

Variable

21.0

None

8.4

2.5

15.4

93.4

-5.7

15.8

73.0

Variable

20.6

Bounded and Limited

8.0

5-9%

2.9

6.9

94.1

19.3

13.9

16.2

None

14.1

< 5%

2.7

-6.1

85.0

-7.0

13.7

LT
LU

0.26

LV

81.2

MT
NL

0.36

PL
PT

0.40

RO
SE

0.42

SI

80.3

Variable

26.7

None

5.0

5-9%

4.9

4.8

94.2

7.7

8.9

67.1

Long term fixed

29.7

High or Unbounded

-7.2

< 5%

0.2

5.2

-11.1

94.0

1.0

16.8

83.8

Variable

26.3

None

20.5

< 5%

0.4

1.5

-5.2

91.7

-1.5

8.7

74.2

Variable

29.0

None

18.5

5-9%

5.6

-15.2

93.5

-3.5

8.4

95.6

Variable

24.5

None

9.3

1.6

-3.9

77.8

-0.4

7.8

41.2

High or Unbounded

11.9

3.1

6.1

82.6

6.8

19.6

None

10.3

3.4

-7.2

82.9

0.4

11.7

2.7

5.9

79.1

0.2

9.1

4.6

7.6

78.7

3.3

12.5

4.5

-3.5

88.9

0.4

13.0

69.6
76.6

SK

Variable

90.5

UK

0.37

64.6

18.0

EU
Average

0.37

76.0

23.8

None

6.3

None

25.2
12.7

< 5%

1.4
0.4

5-9%
0.5

Sources: Eurostat and “Report on Residential Real Estate”, ESRB Expert Group on Real Estate, 2015.

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33

2.9
2.3

2.5
-0.7

1.8

A key indicator in this analysis is the level of mortgage debt due to the risks that
unsustainably high debt can pose to the economy. The accumulation of household debt has
both costs and benefits. Household borrowing facilitates the purchase of investment goods, such as
housing, and allows households to smooth consumption over their life cycle. Hence the option to
accumulate debt improves the welfare of households and wider society. However, high
indebtedness can also be associated with risks, both for individuals and the economy as a whole.
At the individual level, high indebtedness can leave a household more sensitive to shocks. A shock
to cash flow, due to reduced income or increased interest payments, may force a household to cut
back on consumption or in more extreme circumstances renege on its debt. A simultaneous shock
to RRE prices can make this more likely as it reduces the ability of struggling households to escape
debt commitments by selling their property. The consumption of highly indebted households may
respond more to RRE price shocks as they also tend to have higher leverage, which amplifies the
73
impact of the RRE price fall on their net wealth. Even if individual households are rational about
the amount of debt they take on, there may be negative externalities for the whole economy
particularly if the incentives to take on debt are misaligned. Households’ inability to internalise these
aggregate effects means that the optimal combined actions of individual households can have
negative implications for wider economic and financial stability.
In assessing the risks from high household debt, one can distinguish between high debt
levels reached through a long and steady build-up, and those reached through a short burst
of rapid credit growth; both have been important amplifiers of economic shocks. Rapid
growth in credit can exacerbate the risks associated with a high level of debt. A period of rapid
credit expansion is likely to mean that a high share of debt is held by new borrowers who tend to be
more vulnerable to shocks. Credit booms have often been associated with weakening underwriting
standards, underestimation of risk by both lenders and borrowers, an unsustainable rise in RRE
prices, and a rise in short-term wholesale funding by banks. All these factors increase the
vulnerability of the balance sheets of both borrowers and lenders. In addition, a rapid credit
expansion may also have been associated with unrealistic expectations about future income growth
and RRE prices. The reassessment of these expectations following a shock could be associated
with a sharp reduction in the availability of credit. The literature on the role of household credit
focuses on credit growth as an important indicator of the probability and severity of a crisis. This
literature finds strong evidence that a high rate of credit growth increases the likelihood of a crisis
occurring. Moreover, recessions preceded by a sharp increase in indebtedness tend to be deeper
74
and longer than other recessions. Although there is comparatively less literature on the role of the
level of indebtedness, there is convincing evidence that high aggregate debt levels go together with
75
sharper cuts in consumption following a crisis.
The distribution of debt is also very important, given that the biggest risks from household
indebtedness relate to the behaviour of highly indebted borrowers. A range of evidence based
on micro data suggests that highly indebted borrowers cut back consumption more sharply in
response to shocks, and are more likely to struggle to meet their mortgage commitments than other

73

Mian and Sufi (2014) as above fn. 15 show that the sensitivity of consumption to changes in RRE prices is three times
higher for households with loan-to-value ratios over 90% than for those with LTV ratios of less than 30%.

74

See e.g. Drehmann and Juselius (2012) as above fn. 32 and Jordà et al. (2015) as above fn. 10.

75

One such study is Flodén (2014) which shows that consumption between 2007 and 2012 fell by almost 4% more in
countries which at the start of the crisis had a debt-to-income ratio of 200% than in countries that had a DTI ratio of 100%.
See Flodén, M., “Should We Be Concerned by High Household Debt”, 2014: Flodén, M., “Should We Be Concerned by
High Household Debt”, Ekonomistas, February 2014

ESRB
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34

76

borrowers. Whilst the literature supports a link between the aggregate household debt level and
the fall in consumption or severity of a crisis following an initial shock, there is little evidence on the
extent to which aggregate debt plays a role, or whether it is just a summary measure for the share
of highly indebted households. Other distributional factors may also be important when analysing
the risks. These include whether the most highly indebted households hold liquid financial assets,
which can be used to ease shocks to cash flow, and (un-mortgaged) housing wealth, which enables
77
a struggling borrower to trade down. It should also be considered whether highly indebted
households, as measured by DTI ratios, are also the most leveraged in terms of LTV ratios. If so,
this can increase the size of a wealth effect from a fall in RRE prices, magnifying the impact of a
cash-flow shock on consumption.
However, just how risky a specific level of debt is to the economy may vary due to the level
and evolution of certain macroeconomic variables and some of the structural factors
mentioned above. The evolution of these factors in many of the focus countries may suggest that
the sustainable level of debt has increased over the past decades. Under some conditions, a
declining real long-term interest rate, declining credit spreads and increased financial
intermediation are factors that may indicate that the sustainable, or equilibrium, debt level has risen
in many European countries. However, it should be noted that the causes of these developments
may not support a higher equilibrium debt level, for example if interest rates are low due to lower
growth expectations. Real RRE prices are also an important factor affecting the demand and supply
of credit. Because housing accounts for a large proportion of household assets, changes in RRE
78
prices can have a significant wealth effect affecting the demand for credit. Higher RRE prices also
represent more valuable collateral, which can lead to credit expansion by relaxing credit
79
constraints. But the channel can also operate in the opposite direction: increasing credit provision
can lead to rising real estate prices in the short and long run (if housing demand persistently
outstrips demand).
It is important to note that it is not always simple to disentangle long-term developments in
the macroeconomic determinants of the debt level from cyclical developments that will
revert in the medium term. For example, there is some evidence that one of the drivers of rising
household credit in Europe in the past 40 years has been rising RRE prices. The relatively fast falls
in RRE prices that have occurred in some countries in recent years would suggest that a portion of
80
the associated rise in credit had not been for sustainable reasons. The amount of debt that is

76

For evidence on the US, the UK and Denmark, respectively, see Mian and Sufi (2014) as above fn. 15; Bunn, P. and
Rostom, M., “Household debt and spending”, Bank of England Quarterly Bulletin, Q3 2014 Vol 54(3); and Andersen, A.
L., Duus, C. and Jensen, T. L., “Household debt and consumption during the financial crisis”, Monetary Review,
Danmarks Nationalbank, Q1 2014. Further evidence is documented in Financial Stability Report, Sveriges Riksbank,
2015:2, 2015, pp. 13-14.

77

Evidence for Denmark in the post-crisis period found that households with substantial financial assets cut back on
consumption more sharply than households with limited financial assets, though this may have been because they also
suffered greater losses of financial wealth (Andersen et al., 2014 as above fn. 76).

78

Case et al. (2005) find a large housing wealth effect on consumption in a panel of countries including 11 EU countries;
however, for the euro area as a whole, Sousa (2009) shows no housing wealth effect on consumption; for Italian
households, Paiella and Pistaferri (2015) find a large housing wealth effect on consumption. See Case, K. E., Quigley, J. M.
and Shiller, R. J., “Comparing Wealth Effects: The Stock Market versus the Housing Market”, The B.E. Journal of
Macroeconomics, Vol. 5(1), 2005; Sousa, R. M., “Wealth effects on consumption: evidence from the euro area”,
Working Paper Series, No 1050, ECB, 2009; and Paiella, M. and Pistaferri, L., “Decomposing the Wealth Effect on
Consumption”, September 2015.

79

For example, see Bahaj, S. Foulis, A. and Pinter, G., “The Residential Collateral Channel”, 2016.

80

Forthcoming research on the drivers of structural credit; Bianchi, Trinity College Dublin and ESRB Secretariat.

ESRB
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35

considered as sustainable also depends on policymakers’ tolerance of a materialisation of the
associated risks (e.g. a sharper fall in consumption and an increase in defaults in a shock) and their
view of the likelihood and severity of shock scenarios.
Structural and institutional features do not indicate that any focus countries should be
excluded. As mentioned above, structural and institutional features are primarily considered within
the vertical analyses in Section 2.2. However, based on the information illustrated in Table 2.4, one
can conclude that there are both amplifying and mitigating factors relating to structural and
institutional features in all the focus countries with the exception of Denmark, where the numbers in
Table 2.4 suggest that most observed structural and institutional features are mitigating. However,
other factors such as a highly regulated rental market and an inefficient housing tax system suggest
that amplifying features are also present for Denmark and the horizontal indicator-based analysis
also provides a relatively strong signal for Denmark. Based on this, while also recognising the
difficulties in assessing structural and institutional features discussed above, the assessment
suggests that there are no grounds for excluding any of the focus countries from further
assessment based on their structural and institutional features.
Specific vulnerabilities may be rooted in any of the structural or institutional features
mentioned above. This report tries to take all vulnerabilities into account in order to create a
holistic understanding of the vulnerabilities in each country irrespectively of whether the
vulnerabilities are due to cyclical or structural reasons. This suggests that the optimal policy
response is not necessarily to be found (only) in the macroprudential toolbox; in some cases,
vulnerabilities are perhaps best handled with structural reforms, e.g. changes to the regulation of
the rental market or the tax system.

2.1.3

Policy measures to address RRE vulnerabilities

The ESRB has done extensive work on instruments to tackle macroprudential risks originating from
81
the RRE sector. This provides a good basis for understanding and categorising policy measures.
The set of possible real estate instruments can be organised around the three “stretches”
framework employed in the risk analysis section of the report. Table 2.5 shows an indicative
categorisation of macroprudential policy measures by the type of RRE risks that they could directly
address. This is not an exhaustive list of tools to address the different types of risk; countries may
use other tools or certain tools for different purposes.

81

Chapter 3, ESRB (2014) as above fn. 4; ESRB 2015.

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Table 2.5
Macroprudential policy measures, by the type of RRE risks that they could directly address
Identified RRE stretch

Household stretch

Collateral stretch

Banking stretch

Potential tools – depending on
whether addressing stock or flow
of lending

Flow tools:
LTI cap, DTI cap, DSTI cap,
affordability requirements,
amortisation rules

Flow tools:
LTV cap, amortisation rules, term
limits

Flow and stock tools:
Sectoral capital
requirements/increased risk
weights on RRE lending, stress
testing, capital buffers (incl.
countercyclical)

Stock tools:
Sectoral capital requirements/
increased risk weights on RRE
lending, stress testing, capital
buffers (incl. countercyclical)
*
Non-macroprudential policies may
be useful, e.g. tax reforms or rental
market reforms

Stock tools:
Sectoral capital requirements/
increased risk weights on RRE
lending, stress testing, capital
buffers (incl. countercyclical)
*
Non-macroprudential policies may
be useful, e.g. tax reforms or rental
market reforms

Household stretch instruments, such as caps on loan-to-income, debt-to-income and debt serviceto-income ratios, limit the loan amount relative to the income of the borrower and may therefore be
helpful in dampening credit growth. Collateral stretch instruments, such as LTV caps or
amortisation limits, ensure some degree of protection before losses reach lenders’ balance sheets
or before consumption is scaled back, and limit the impact of risks if they materialise. Banking
stretch instruments relate to regulatory capital requirements imposed on banks’ RRE exposures
and aim to limit the impact of risks when they materialise by enhancing the loss-absorbing capacity
of banks. The ESRB Expert Group on Real Estate assessed that a combination of instruments,
addressing different specific risks and channels, often seems to be the most suitable and
82
comprehensive response to vulnerabilities originating in the real estate sector.
A carefully conceived design is crucial to the instruments’ effectiveness and for reducing the risk of
leakages and unintended consequences. Policy design includes aspects such as definitions used
(e.g. as regards the type of income included or how the collateral is valued), exemptions granted
and calibration. A wide array of methods is potentially available to help calibrate instruments. The
methods vary in their degree of complexity and data intensity, ranging from simple descriptive
analysis to advanced models. While such methods can usefully inform the setting of an instrument,
expert judgement still remains crucial given the complexity involved in fully grasping the systemic
risks and the uncertainty surrounding the likely impact of the instruments.
The role of policy more broadly than just macroprudential policy was also discussed in the 2015
report by the ESRB Expert Group on Real Estate. Policies that affect the structural features of RRE
markets might positively contribute to financial stability since these features may amplify or dampen
the transmission channels between the housing market, real economy and financial sector. Thus,
rather than tackling emerging cyclical imbalances in markets through macroprudential intervention,
policies influencing structural characteristics of RRE markets might positively contribute to financial
stability. Such policies could address the tax treatment of housing/mortgage tax deductibility, the
regulation of rental markets or regulatory constraints on developing new housing.
Member States’ implementation of measures differs along most dimensions and, as measures in
most cases have only recently been introduced, the evidence for determining “best practice” is still

82

ESRB 2015.

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37

relatively scarce. In practice, a combination of instruments, even if not applied simultaneously, is
the general rule, in particular for collateral and income stretch instruments.

Policies targeted at household indebtedness
As mentioned in Section 2.1.2 above, an unsustainably high debt level can pose risks to the
economy and financial system. Therefore, it is useful to consider which policy measures might be
useful to address the vulnerabilities that may arise from a high stock of mortgage debt.
A range of policy tools can be used to address the risks of high indebtedness. In principle, any
measure that increases the cost of debt or reduces the amount of debt available to households can
be used to lower the level of debt. Moreover, several tools – including macroprudential tools, tax
measures and other tools – can be used to lower the riskiness of a given level of debt. It is
important to note the benefits and costs of using the various policy options.
Macroprudential policies
Several macroprudential tools can be used to lower household indebtedness. These tools can be
categorised into measures that are directed towards the loan contract between a lender and
borrower (borrower-based measures) and measures targeted at the lender itself (lender-based
measures).
Measures that set limits on certain characteristics of mortgage loans (such as LTI or LTV caps)
have a direct impact on the flow of credit. As the characteristics of a loan contract cannot typically
be adjusted unilaterally, these measures will normally only affect new or recontracted loans.
Tools on bank capital, such as sectoral capital requirements for residential real estate, are aimed at
strengthening bank rather than household balance sheets. Higher (sectoral) capital requirements
may be less effective than borrower-based tools in curbing the flow of new loans as they do not set
a strict limit. Although there is some empirical evidence that borrower-based tools are most
effective in reining in credit growth, most studies find that both borrower-based and lender-based
83
instruments can impact credit growth. However, as macroprudential capital requirements apply
84
only to banks, these measures may be circumvented by non-bank lending.
Tax measures and other tools
Where high debt levels are caused by institutional and structural factors, policy measures can be
directed at changing these factors. Such options should also be taken into account, even if most of
these reforms are not in the toolkit of macroprudential authorities. These measures can directly
affect household indebtedness, for example by increasing the cost of borrowing or the supply of
housing. And they can lower the riskiness of a given level of indebtedness by reducing the volatility
of RRE prices.

83

See e.g. Cerutti, E., Claessens, S. and Laeven, L., “The Use and Effectiveness of Macroprudential Policies: New
Evidence”, IMF Working Paper WP/15/61, 2015; Claessens, S., Ghosh, S. R. and Mihet, R., “Macro-Prudential Policies
to Mitigate Financial System Vulnerabilities”, IMF Working Paper WP/14/155, 2014; and Kuttner, K. N. and Shim, I.,
“Can non-interest rate policies stabilise housing markets? Evidence from a panel of 57 economies”, BIS Working
Papers No 433, 2013.

84

For cross-country evidence on cross-sector substitution following macroprudential policies, see Cizel, J., Frost, J., Houben,
A. and Wierts, P., “Effective Macroprudential Policy: Cross-Sector Substitution from Price and Quantity Measures”,
IMF Working Paper WP/16/94, 2016.

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38

For example, since countries with high stocks of debt are generally characterised by a preferential
tax treatment of mortgage debt, such as mortgage interest deductibility (MID), reducing MID can be
an effective and efficient way of reducing the level of household debt and can affect both the stock
of existing debt and the flow of new loans.
Another way to reduce debt levels is by encouraging existing borrowers to amortise more. Even
though binding amortisation requirements can in general only be applied to new loans, amortisation
of existing loans can also be stimulated through other measures, such as tax incentives for
amortising mortgages and moral suasion by banks and authorities.
Ensuring an adequate supply of housing and a well-functioning rental market may also reduce
indebtedness and the volatility of RRE prices. A structural shortage in housing supply increases
RRE prices and may induce households to borrow more. This may increase both the aggregate
level of indebtedness and the share of highly indebted households.
The choice between different policy measures depends on the effectiveness of a measure in
mitigating specific risks and the potential economic costs. In calibrating macroprudential and other
tools to address (the risks from) high household debt, policymakers should be specific about the
risks they want to address and the policy objective they want to achieve. For instance, lowering the
aggregate level of indebtedness may call for different policy measures than those for reducing the
proportion of households with excessive debt. Moreover, the effectiveness of a measure should be
weighed against the possible negative economic effects in terms of restricted financial
intermediation and lower growth. Measures that affect all borrowers can be more effective than
measures that only affect new borrowers, but may also involve higher short-term economic costs.
Analysis produced by the IMF shows that some policies have proved to be more effective than
others in reducing mortgage credit growth and RRE price inflation in advanced economies in the
.85
past two decades Chart 2.2, which is taken from the IMF (2014) analysis, shows that DTI limits
have constrained mortgage credit growth the most, followed by tightening mortgage tax policies
and an LTV limit. Similarly, tightening mortgage tax policies can have a significant impact on RRE
price inflation.

85

See Section B of 'Macroprudential Policy: Lessons from Advanced Economies' in IMF Country Report No 14/234, July
2014.

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39

Chart 2.2
IMF event study estimates of the impact of macroprudential tools on mortgage credit and
86
house prices
a) Reduction in mortgage credit growth in
response to macroprudential measures

b) Reduction in house price inflation in response
to macroprudential measures

(percentage change)

(percentage change)

1.6

4.0

1.4

3.5

1.2

3.0

1.0

2.5

0.8

2.0

0.6

1.5

0.4

1.0

0.2

0.5

0.0

0.0
DTI

tax

LTV

RW

other

tax

RW

LTV

DTI

other

Source: IMF staff calculations (2014).

In general, the macroeconomic costs associated with policy measures are lower when policies are
applied gradually. However, the (short-term) economic costs may not be the same at each point in
time. For instance, household deleveraging may be more costly in a period of weak economic
demand, whereas reducing mortgage interest deductibility will be less costly when interest rates are
low.

2.1.4

Summary: results of the horizontal analysis

As described earlier, a cross-country risk identification comprising an indicator-based scoreboard,
and analysis of the cyclical position of vulnerabilities and institutional/structural features, was
applied to all 28 EU Member States in order to identify a set of focus countries for further
investigation. The three-step approach to horizontal risk identification was initially applied in the
fourth quarter of 2015 and led to the identification of ten countries: Austria, Belgium, Denmark,
Estonia, Finland, Luxembourg, the Netherlands, Slovakia, Sweden and the United Kingdom. In
early 2016, during the course of the assessment, Malta was also confirmed as a focus country
bringing the total to eleven.
For the purpose of this report, the scoreboard and cyclical analysis were updated with the latest
available data (for August 2016) and some small methodological adjustments have also been made
since the initial horizontal analysis was performed. The current scoreboard and charts may
therefore suggest a slightly different set of high-risk countries than those originally identified and

86

Figure 3, ibid.

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40

analysed by the ESRB (in Section 2.2). Nevertheless, the originally identified focus countries
continue to exhibit vulnerabilities in the latest data, which supports the robustness of the original
identification. It is also useful to see how risks may have developed in other EU countries over the
course of the assessment process.
Section 2.2 will discuss the results of the vertical analysis for the eleven focus countries in more
detail.

2.2

Vertical analysis of RRE vulnerabilities

The horizontal analysis – described in Section 2.1 of this report – identified those countries with
vulnerabilities that have the potential to become material risks in the medium term. This set of focus
countries was then subject to in-depth, country-specific analysis in a second stage of the work
(known as the “vertical analysis” stage).
This section provides the preliminary vertical analysis of vulnerabilities related to residential real
estate, taking into account whether prudential policy measures as well as other relevant policies
enacted are likely to address the vulnerabilities in the medium term. This analysis has been
prepared jointly by the ESRB Secretariat and the members of the task force who were responsible
for the country analysis (the Country Teams), with input from the ESRB Assessment Team on
Macroprudential Measures and methodological advice from the ESRB Working Group on Real
Estate Methodologies (the “Methodology Team”). This team-based framework was developed to
ensure a fair and independent treatment of each country, so that all relevant factors are taken into
account. Country representatives were heavily involved in the process and have provided input via
self-assessments, via interactions with the task force and at ESRB meetings in order to ensure the
accuracy and completeness of the analysis. A more comprehensive description of the
organisational framework can be found in Annex A.
Section 2.2.1 briefly describes the methodology for the vertical assessment and Section 2.2.2
presents the country-specific analysis for each of the eleven focus countries.

2.2.1

Vertical analysis methodology

A qualitative approach was taken to analyse vulnerabilities and policies at the country level. The
analysis was organised around the three “stretches” described in Section 1.3; each identified
87
vulnerability was assigned to the associated stretch. The overall analysis was then based on the
vulnerabilities in each stretch and the interaction between them, since one type of vulnerability may
amplify other types. At the country level, consideration was given to the interaction of the stretches,
as well as structural features, relevant policy measures and other country specificities. Note that, in
addition to prudential policies, non-prudential policy measures were also investigated if they were
deemed to be potentially important for RRE markets (see Section 2.1.4). Policy measures were
taken into account in the assessment if they have been implemented (including with a transitional
period) or decided upon with a firm plan for implementation.

87

This methodology was inspired by a concept put forward by the ESRB Expert Group on Residential Real Estate (ESRB
2015).

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As described in Section 2.1.2, in each country there are a number of structural features that may
either amplify or reduce RRE vulnerabilities; the advantage of conducting in-depth country analysis
is that these features can be taken into account. Since material risks to financial stability can arise
as a result of structural and cyclical factors, both are investigated in the country analysis. The
assessment of whether the enacted policy in each country addresses any vulnerabilities in the
three stretches has resulted in a grading of policy at the level of each stretch and overall for a
country. Note that credit could be given to the same policy measure more than once if it was
considered that it could address vulnerabilities in more than one stretch. Two main criteria were
88
used to assess the policy stance:
•

Appropriateness: whether or not policies are conceptually suitable given the nature and
timing of risks. Appropriate measures are those which address the risks in that country, e.g. if
there are risks related to a country having a high debt-to-income ratio, an appropriate
measure could be a DTI or LTI limit.

•

Sufficiency: whether or not policies are expected to or could be shown to significantly
mitigate, or reduce the build-up of, risks over an appropriate time horizon with a limited
unintended impact on the general economy. Factors to be considered when assessing policy
sufficiency relate to the calibration of the measure, its timeliness and its scope of application.
If there was evidence that the measure was having the intended effects and was mitigating or
reducing the identified risk(s), and/or if it was causing any unintended negative effects, this
has been taken into account.

The policy stances of the focus countries were assessed individually for each of the three stretches
and then an overall assessment was made.
At the level of each stretch (household, collateral, banking), there were four possible assessment
grades:
1.

Appropriate and sufficient, where policies are conceptually suitable given the nature and
timing of risks and where the level and build-up of risks can be shown to be fully addressed by
the policy packages.

2.

Appropriate and expected to be sufficient, where policies are conceptually suitable given
the nature and timing of risks and where the level and build-up of risks cannot be shown, but
are expected, to be addressed by the policy packages.

3.

Appropriate but not expected to be sufficient, where policies are conceptually suitable
given the nature and timing of risks, but where the level and build-up of risks are not expected
to be addressed by the policy packages.

4.

Not appropriate, for cases where no conceptually suitable measures, given the nature and
timing of risks, have been taken.

The grading of an individual country’s policy measures into one of the four categories followed a
two-step procedure. The first step was to see whether any policies have been taken to address the
risks identified. If not, the policy stance was assessed as not appropriate (option 4), but if
conceptually suitable measures have been taken, the policy stance was assessed to be appropriate
(options 1-3). In cases where appropriate policies have been taken, the next step was to group the

88

The conceptual criteria and precise definitions were proposed by the RRE Methodology Team.

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policy stance into categories 1-3 taking into account the calibration of the measures, the timeliness
and the scope of application. If there is evidence that measures have had the intended effects and
are mitigating or reducing the identified risk(s), and/or if they are causing any unintended negative
effects, this was taken into account.
When an assessment had been arrived at for each of the three stretches, an overall assessment of
the country’s policy strategy was performed using the following aggregation rule:
•

If the policy strategy was assessed to be not appropriate for any individual stretch, the overall
policy strategy was assessed as not appropriate.

•

If the policy strategy was assessed to be appropriate for all three stretches, the sufficiency of
the overall policy strategy was determined by the lowest sufficiency grading of the individual
stretches (where the highest grading is category 1, and the lowest is category 3).

2.2.2

Country analysis

Austria
Key points
Vulnerabilities for Austria are related to the robust growth, particularly recently, in RRE prices and
mortgage credit and the risk of a further loosening in lending standards. The vulnerabilities in the
collateral stretch are mostly due to the rapid increase in RRE prices since 2011. Until recently, RRE
price dynamics were much stronger in Vienna than in the rest of the country. However, since Q3
2014, RRE prices have been rising more quickly in the rest of the country (where the annual growth
rate was 8.9% in Q1 2016) than in Vienna itself (where the annual growth rate was 6.5% in Q1
2016). In general, rapid RRE price growth that surpasses household income growth, as has
recently been observed in Austria, makes it more difficult for households to become homeowners,
and can lead to an overall increase in household indebtedness and/or a rise in the size of the group
of highly indebted households. The Oesterreichische Nationalbank (OeNB) estimated that RRE
prices in Vienna were 22.8% above the price suggested by fundamentals in Q1 2016, whereas the
prices in the whole country were more in line with fundamentals at 6.3% above fundamentals (see
Chart AT.1). The valuation measures are partly driven by the fact that RRE prices in Austria have
been growing compared with some fundamentals. For instance, the price-to-income index rose to
127% in Q1 2016 from 100% in 2010, while during the same period the average EU PTI decreased
by 1 p.p. Moreover, the price-to-rent index increased to 113% in Q1 2016 from 100% in 2010, while
the EU average decreased to 97%.
The strong RRE price dynamics have coincided with robust credit growth more recently. In June
2016 loans for house purchases grew by 5% annually. The OeNB gathers data on banks’ lending
standards via a survey. Unfortunately these data are not completely reliable since there are a
number of caveats for the survey: (1) it covers only a relatively small market share (about 20-25%
of housing loans collateralised by residential real estate); (2) its sample size changes over time;
and (3) the variance in the data between banks is quite large, also due to different methods of
calculation between banks. For this reason, the results have to be carefully interpreted. However,
the first indications of the survey suggest that vulnerabilities appear to be increasing. The data
suggest that the sample average median DTI ratio for new mortgages among surveyed banks
increased to 490% in Q4 2015 from around 400% in Q4 2014, while the sample average median
LTV ratio increased to 65% in Q4 2015 from 60% in Q4 2014 (see Chart AT.3). However, the share

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of the volume of new loans with LTV ratios above 90% increased between Q1 2013 – Q2 2014 and
Q3 2014 – Q4 2015. Furthermore, 67% of the volume of new loans had a DTI above 400% in Q4
2015. Given the available evidence, the DSTI ratio has been stable. For the sample average
median DTI ratio, the change was in particular driven by two medium-sized banks, of which only
one reported data as of Q3 2014. Excluding these banks from the sample leads to a sample
average median DTI ratio of 440% instead of 490% in Q4 2015. The variance between banks is
relatively large.
As a response to rising vulnerabilities related to the real estate sector, suggested in particular by
89
the first indications of the above-mentioned OeNB survey on lending standards , the OeNB
informally communicated expectations to the industry on lending standards at end-July and in early
August. Such moral suasion aims to reduce, ex ante, the likelihood that lending standards will be
loosened to an extent that would increase systemic risk. Furthermore, on 1 June 2016, the Austrian
Financial Market Stability Board (FMSB) issued advice to the Federal Minister of Finance to
prepare the legal foundations for imposing limits on LTV, DTI or DSTI ratios in new lending. Such
an expansion of the macroprudential toolkit is meant to ensure that the FMSB can act on systemic
risks arising from real estate-related vulnerabilities.
When analysing the nature of the identified vulnerabilities, one can observe both mitigating and
aggravating factors. The identified aggravating factors relate to the significant shares of variable
rate loans (for both new loans and in the existing stock) as well as existing foreign currency housing
loans. However, the share of both variable rate loans and foreign currency loans has been
declining. Also, several analyses show that particularly borrowers with foreign currency housing
loans in Austria hold considerable risk buffers that mitigate related vulnerabilities. Mitigating factors
include a relatively low home-ownership rate, which has been stable for decades, combined with a
well-developed rental market. Moreover, most of the mortgages are amortising, while the proportion
of mortgage holders among homeowners is close to the EU average (in 2014 25% of homeowners
had mortgages in Austria, compared with 27% for the EU as a whole). Mortgage loans in relation to
GDP as well as to Austrian banks’ Tier 1 capital are low compared with other EU countries. Total
household indebtedness in relation to GDP is a bit lower but close to the median for the EU and
has declined slightly over the last few years. In addition, the wealthiest households tend to be the
households with the highest levels of debt. The relatively high housing investment in Vienna may
90
also be viewed as a mitigating factor. Tax deductibility of mortgage interest payments is
negligible. An increase in the real estate transfer and capital gains tax in 2016 may make real
estate purchases for investment purposes marginally less attractive in the long run and may
therefore mitigate future RRE price appreciation pressures. Finally, exposures of Austrian banks to
RRE receive risk weights above the EU average, which makes the Austrian banking sector
relatively better capitalised to absorb potential losses from RRE shocks. However, the overall
solvency ratio of the Austrian banking sector is below the EU average.
Given RRE price dynamics and valuations (particularly in Vienna), coupled with robust growth of
mortgage loans and signs of weakening lending standards, vulnerabilities in the Austrian RRE
sector are building up, particularly in the collateral and household stretches. Indeed, the first

89

Some caveats apply to the OeNB survey data: (1) it only covers a relatively small market share (about 20-25% of housing
loans collateralised by residential real estate); (2) its sample size changes over time; and (3) the variance in the data
between banks is quite large. For this reason, the results must be interpreted with care.

90

The housing stimulus package for the development of subsidised rental homes in the next five years may further ease
demand pressures.

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91

indications of the recent OeNB survey show that for some banks a large share of the volume of
new loans represent high levels of debt compared with the house values and borrower income. In
these types of situations, borrower-based macroprudential tools could efficiently prevent the
excessive build-up of vulnerabilities and systemic risk going forward. Even though expectations
have been communicated informally and steps have been taken to make the policy instruments
92
legally available, they are currently not available in the legislation to the Austrian authorities.
Hence, the authorities would not be able to respond quickly to growing vulnerabilities by using legal
borrower-based macroprudential measures if they found it to be necessary.
While the policy measures that have been taken by the Austrian authorities are appropriate given
the nature of RRE vulnerabilities in Austria, they may not be sufficient to fully address them.
Measures introduced by the Austrian authorities include the expectations regarding sustainable
93
lending standards that have been communicated to banks. In addition, the FMSB has advised the
Ministry of Finance to extend the macroprudential toolkit to borrower-based macroprudential
instruments in the field of real estate financing to ensure that the FMSB can act on systemic risks
94
arising from unsustainable real estate market developments. Despite the measures taken, RRE
prices and mortgage credit are growing robustly, there are groups of households with elevated debt
levels and there is some evidence of weakening lending standards. The measures taken for the
banking stretch seem sufficient to deal with RRE vulnerabilities relating directly to the banking
system. However, given the developments in RRE prices and credit, the measures taken for the
collateral and housing stretches may not be sufficient. Appropriate measures have been taken for
all stretches.

91

See footnote 89: some caveats apply to the OeNB survey data.

92

Following the ESRB’s decision to issue this warning, the Austrian Financial Market Stability Board discussed sustainable
lending standards in residential real estate during its meeting on 23 September 2016. See the FMSB press release: FMSB
press release.

93

See footnote 92.

94

The FMSB’s advice is available publicly: https://www.fmsg.at/en/publications/warnings-andrecommendations/advice-2-2016.html.

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Table AT.1
Summary assessment – Austria
Summary RRE risk
assessment narrative

Key vulnerabilities are related to the collateral and household stretches
Vulnerabilities for Austria are related to robust growth, particularly recently, in RRE prices and mortgage credit and
the risk of a further loosening in lending standards.
RRE prices are increasing rapidly, in particular since 2011. In Q1 2016, RRE prices increased by 8.9% (year-onyear) in Austria outside Vienna and by 6.5% in Vienna, and are now above the pre-crisis level in Austria.
Overall, RRE prices in Austria are broadly in line with fundamentals, but have increased quickly relative to some
fundamentals (e.g. the PTI ratio increased by 27% between Q1 2010 and Q1 2016). At the same time, RRE prices
in Vienna appear to be above fundamentals (by 22.8% in Q1 2016) according to OeNB models.
Housing credit is growing robustly (loans for house purchase grew by 5% in June 2016 over the year). At the same
time, the first indications, which must be interpreted with care, of an OeNB survey indicate a decline in lending
standards.95
The related data suggest that the sample average median DTI ratio among surveyed banks increased to 490% in
Q4 2015 from around 400% in Q4 2014 for new mortgages, while the sample average median LTV ratio for new
mortgages increased to 65% in Q4 2015 from 60% in Q4 2014. However, the share of the volume of new loans
with LTV ratios above 90% increased between Q1 2013 – Q2 2014 and Q3 2014 – Q4 2015. Furthermore, 67% of
the volume of new loans had a DTI ratio above 400% in Q4 2015. Given the available evidence, the DSTI ratio has
been stable.
The share of variable rate and foreign currency mortgages in the stock of loans is still significant despite declining.

Policy assessment given
risks

The policy stance is appropriate but not expected to be sufficient for the collateral and household
stretches
While the policy measures that have been taken by the Austrian authorities are appropriate given the nature of
RRE vulnerabilities in Austria, they may not be sufficient to fully address them.
Despite the measures taken, RRE prices and mortgage credit are growing robustly, there are groups of households
with elevated debt levels and there is some evidence of weakening lending standards.
Even though soft measures have been taken and steps have been taken to make policy instruments legally
available, there is a lack of borrower-based macroprudential tools in the law. These measures could effectively
prevent an excessive build-up of vulnerabilities and systemic risk.
The measures taken for the banking stretch seem sufficient to deal with RRE vulnerabilities relating directly to the
banking system. However, given the developments in RRE prices and credit, the measures taken for the collateral
and housing stretches may not be sufficient. Appropriate measures have been taken for all stretches.

Table AT.2
Summary of risks and policy measures – Austria

Household stretch

Collateral stretch

Banking stretch

Summary risk
assessment/main risks

Housing credit is growing robustly at 5%,
with signs of weakening lending standards
(based on the results of an OeNB survey
96
which must be interpreted with care ). The
sample average median DTI ratio for new
loans increased to 490% in Q4 2015. At
the same time, 67% of the volume of new
loans had a DTI ratio above 400%. A
significant share of mortgage loans are in
foreign currency or are with variable rates,
but this share is decreasing.

RRE prices are increasing
quickly in Austria and prices,
particularly in Vienna, are
estimated to be overvalued. The
RRE price increase has
probably not been driven by a
credit boom. However, recent
RRE price increases in the rest
of the country, the growth in
new housing loans and a
possible deterioration in lending
standards suggest that
vulnerabilities are building up.

The share of mortgages on
banks’ balance sheets is
relatively low (28% in Q1 2016),
which makes banks less
vulnerable to RRE shocks.
Moreover, banks apply above
EU average risk weights to RRE
exposures (the average risk
weight for Austrian IRB banks is
24% as against an EU average
of 16%). However, the
capitalisation of Austrian banks
is lower than that of their EU
peers (the CET1 ratio for Austria
was 12.8% in Q1 2016 as
against an EU average of
13.9%).

Summary of policy
measures (implemented,
planned, under
consideration)

An information folder on the risks of foreign
currency lending has been published (in
2006 and 2011) and the authorities have
made recommendations on minimum
standards for banks’ lending addressing
excessive risk concentration, maturity

LTV limits in certain market
segments: bonds covered by
mortgages (LTV max. 60%),
mortgage loans granted by
building societies (LTV max.
80%) and mortgages included in

Systemic risk buffer (SRB) of up
to 2% for 12 banks (buffer of up
to 1% for systemic vulnerability
and up to 1% to address
systemic cluster risk; in place
since 1 January 2016 with a

95

See footnote 89: some caveats apply to the OeNB survey data.

96

See footnote 89: some caveats apply to the OeNB survey data.

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transformation and foreign currency
lending growth (implemented and
reinforced in 2003, 2010 and 2013).
The OeNB has informally communicated
expectations to the industry on lending
standards (July and August 2016).
There is a lack of macroprudential
instruments available to the Austrian
authorities. The macroprudential toolkit
does not yet include DTI and DSTI
measures. On 1 June 2016 the Financial
Market Stability Board issued advice to the
Ministry of Finance to extend the
macroprudential toolkit to borrower-based
macroprudential instruments in the field of
real estate financing.

Assessment of policy
measures

Appropriate but not expected to be
sufficient

the coverage funds in the
insurance sector (LTV max.
60% to be included in the
coverage fund).
The OeNB has informally
communicated expectations to
the industry on lending
standards (July and August
2016).
There is a lack of
macroprudential instruments
available to the Austrian
authorities.
The macroprudential toolkit
does not yet include LTV
measures. On 1 June 2016 the
Financial Market Stability Board
issued advice to the Ministry of
Finance to extend the
macroprudential toolkit to
borrower-based
macroprudential instruments in
the field of real estate financing.
Appropriate but not expected
to be sufficient

phase-in until end-2018)
Other systemically important
institution (O-SII) buffer of
between 1% and 2% (active
from 1 June 2016 with a phasein until end-2018)
The capital conservation buffer
is being gradually introduced
between 2016 and 2019. When
fully phased in, it will stand at
2.5%.

Appropriate and sufficient

Household stretch
The annual growth rate of housing loans is robust; it has increased from 1.6% in May 2013 to 5% in
June 2016 (see Chart AT.2). In comparison, the growth rate for housing loans was 2% in the euro
area in June 2016. In the period 2009-15, the average yearly growth rate was 3% in Austria, which
is lower than the growth rate prior to the crisis (in the period 2005-8 the average yearly growth rate
was 8.1%).
In general, households that are highly indebted relative to income or the value of their property
could be particularly vulnerable to economic shocks such as an increase in unemployment or a fall
in household incomes or RRE prices. Under such circumstances, households may find it more
difficult to service their debts and the number of mortgage defaults may increase, leading to direct
credit losses for banks, especially in the event of a fall in RRE prices. Moreover, if an adverse
scenario for the economy does materialise, the associated negative household income and wealth
effects may reinforce the initial shock, further enhancing the negative direct and indirect effects on
financial stability (e.g. if households need to reduce consumption in order to service their mortgage
loans).
97

The OeNB argues that part of the peak in the issuance of new loans for housing in recent years
(that has now receded) might have been caused by the restructuring of foreign currency loans as
well as the refinancing of fixed rate loans (see Chart AT.2). However, there is a limited amount of
fixed rate loans. Historically, a low home-ownership rate and a low share of mortgage holders
among homeowners have maintained household indebtedness at a low level (51% of GDP in Q1
2016 compared with an EU average of 53%). The low home-ownership rate is combined with a
well-developed rental market. Around 25% of Austrian homeowners had mortgages in 2014
98
compared with 27% for the EU. In addition, according to the 2014 data taken from the

97

These are purely new loans; they exclude loans that are refinanced within a bank, but for technical reasons they do not
exclude loans that are refinanced across the banks.

98

Other data from the 2014 Household Finance and Consumption Survey suggest that 34% of Austrian homeowners have a
mortgage. The 25% is taken from the ECB Statistical Data Warehouse.

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Eurosystem’s Household Finance and Consumption Survey, household debt and wealth appear to
go hand in hand, so that the most indebted households are also the wealthiest. Furthermore, most
mortgage holders are amortising their loans.
99

The first indications of an OeNB survey on lending standards, even though based on a relatively
small sample of banks, indicate that vulnerabilities in the household stretch appear to be
increasing. But, since the variance between banks is quite large and the sample size is small and
changes over time, these results have to be interpreted with care. The data suggest that the
sample average median DTI ratio among surveyed banks increased to 490% in Q4 2015 from
around 400% in Q4 2014 for new mortgages (see Chart AT.3). In addition, 67% of the volume of
new loans had a DTI ratio above 400% in Q4 2015 (the share of the number of loans with a DTI
ratio above 400% was 49%). Given the available evidence, the DSTI ratio has been stable at
around 25%. However, such analysis is subject to uncertainty and should be interpreted with care
due to the short availability of the underlying data and the relatively small and changing sample size
100
of six banks, though covering the different banking sectors. The OeNB argues that the increase
in DTI ratios and LTV ratios is partly due to an extension of the sample size.
101

As a response to these first indications of deteriorating lending standards , the OeNB has
102
communicated to the banking industry informal expectations regarding lending standards. The
Austrian macroprudential toolkit does not yet include any legal borrower-based instruments.
However, on 1 June 2016, the FMSB issued advice to the Ministry of Finance to extend the
macroprudential toolkit to borrower-based macroprudential instruments in the field of real estate
103
financing.
Another financial stability vulnerability related to the household stretch stems from a high legacy
share of foreign currency loans and a high share of variable rate loans. In May 2016 the share of
foreign currency loans in the stock of housing loans was 15%, particularly denominated in Swiss
francs. Moreover, almost 80% of total loans are with variable interest rates (see Charts AT.4 and
AT.5). Due to the high share of variable interest rate loans and foreign currency loans, most
Austrian mortgagors are exposed to interest rate risk and some of them to foreign currency risk.
A potential increase in interest rates may result in a reduced repayment capacity of many
mortgagors, as could significant movements in the relevant currency for those with foreign curreny
loans. These risks are mitigated by the limited level of indebtedness of Austrian households.
As regards foreign currency loans, around 83% of foreign currency borrowers have above median
wealth and income. Also, the risk of foreign currency lending to private households has been
targeted by the Austrian competent authorities with several measures since 2003 and banks no
longer offer foreign currency loans domestically. The measures taken range from the publication of
an information folder on the risks of foreign currency lending to the implementation and
reinforcement of minimum standards addressing excessive risk concentration, maturity
transformation and foreign currency credit growth (minimum standards (2003, 2010, 2013),
information leaflet (2006, 2011), letter from the FMA to banks (2008), moral suasion and

99

See footnote 89: some caveats apply to the OeNB survey data.

100

Unfortunately, the survey does not provide any breakdown by loans secured by property located in Vienna and the rest of
the country. For the next round of the survey, this enlargement may be considered.

101

See footnote 89: some caveats apply to the OeNB survey data.

102

See footnote 92.

103

See footnote 94.

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regular/ongoing management talks. Regarding variable rate mortgages, banks increasingly
advertise fixed rate loans according to anecdotal evidence gathered by the OeNB.
As a consequence of the policy measures taken, the share of foreign currency loans has been
decreasing; in Q1 2016 the share of foreign currency loans in new lending was less than 1%.
Moreover, the share of loans with an interest rate fixation period of up to one year in new lending
was 63% in May 2016, which is a decrease of 8.5 p.p. over a one-year horizon and 20 p.p. over a
two-year horizon. However, in Q1 2016, 25% of the foreign currency loans had a residual maturity
of over 15 years according to the OeNB (down from 52% in 2007). The IMF pointed out in 2013 that
the long residual maturity of these loans makes the risks connected to them limited, as the potential
interest rate and foreign exchange shock can be absorbed with a low level of provisioning.
Additionally, banks no longer offer foreign currency loans domestically.
Overall, the low level of aggregate household indebtedness and the fact that most mortgage
holders are amortising their loans are factors that mitigate vulnerabilities related to household
stretch. However, a high legacy share of foreign currency loans and the high share of variable rate
loans are factors amplifying vulnerabilities. The Austrian authorities have targeted the foreign
currency loans with several measures and, as a consequence, their share is decreasing, also
because banks in Austria no longer offer foreign currency loans domestically.
Given the current level and dynamics of vulnerabilities in the household stretch, the measures
104
taken are deemed appropriate, but may not be sufficient. First indications on lending standards ,
though based on a relatively small sample of banks, suggest a potential build-up of vulnerabilities
related to the distribution of DTI ratios and DSTI ratios for new loans. This development has led the
OeNB to communicate informal expectations to the banks. However, these expectations were
communicated only very recently and there is no hard data available to assess whether they have
been effective and complied with. Furthermore, they are merely informal and are expectations
rather than recommendations. Due to the lack of available legal instruments, the Austrian
authorities are unable to act efficiently with direct borrower-based macroprudential tools if needed.
Legally binding limits on lending standards would be more effective in preventing a potential buildup of vulnerabilities related to loosening lending standards going forward.

Collateral stretch
Vulnerabilities in the collateral stretch are mostly due to the rapid increase in RRE prices since
2008. Until recently, RRE price dynamics were much stronger in Vienna than in the rest of the
country. However, since Q3 2014, RRE prices have been rising more quickly in the rest of the
country (where the annual growth rate was 8.9% in Q1 2016) than in Vienna itself (where the
annual growth rate was 6.5% in Q1 2016). The OeNB has estimated that RRE prices in Vienna
were overvalued by 22.8% in Q1 2016, whereas the overvaluation in the whole country was more
muted at 6.3% (see Chart AT.1). The overvaluation measures are partly driven by the fact that RRE
prices in Austria have been growing compared with some fundamentals. For instance, the price-toincome index rose to 127% in Q1 2016 from 100% in 2010, while during the same period the
average EU PTI ratio decreased by 1 p.p. Moreover, the price-to-rent index increased to 113% in
Q1 2016 from 100% in 2010, while the EU average decreased to 97%. In general, rapid RRE price

104

See footnote 89: some caveats apply to the OeNB survey data.

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growth that surpasses household income growth, as has recently been observed in Austria, makes
it more difficult for households to become homeowners, and can lead to an overall increase in
household indebtedness and/or an increase in the size of the group of households with elevated
debt levels. However, according to measures calculated by the OeNB, the affordability of housing
has recently been stable in Vienna and has been decreasing in the rest of the country.
Low household indebtedness suggests that there has been a limited role of credit and a quite
significant role of cash buyers in the RRE price appreciation in Vienna. Furthermore, the low homeownership ratio, the positive net migration and the increasing number of households in Austria are
mitigating the vulnerabilities in the collateral stretch.
105

The above-mentioned OeNB survey on lending standards, even though based on a relatively
small sample of banks, indicates that vulnerabilities appear to be increasing in the collateral stretch.
However, since the variance between banks is quite large and the sample size is small and
changes over time, these results have to be interpreted with care. According to the OeNB survey,
the sample average median LTV ratio among surveyed banks for new loans increased from 60% to
65% between Q4 2014 and Q4 2015 (see Chart AT.3). Regarding the dynamics of the LTV
distribution of new loans, the share of the volume of new loans with LTV ratios above 90%
increased between Q1 2013 – Q2 2014 and Q3 2014 – Q4 2015. The OeNB notes that loans in the
highest LTV class usually have higher additional collateral. Other data from the ECB Bank Lending
Survey suggest that banks’ lending standards for loans for house purchase have been unchanged
or even tightened slightly over the last three months and are expected to remain stable over the
following three months.
106

In order to counter a possible weakening of lending standards, the OeNB communicated informal
expectations regarding sustainable lending standards to the banking industry. These expectations
appear to be stringent, but are merely informal and are expectations rather than actual
recommendations. As for the household stretch, legally based limits would be more effective in
preventing a build-up of vulnerabilities related to loosening lending standards.
Beyond the above measures, the Austrian authorities have set LTV limits in certain market
107
segments : bonds covered by mortgages (LTV max. 60%), mortgage loans granted by building
societies (LTV max. 80%), and mortgages included in the coverage funds in the insurance sector
(LTV max. 60% to be included in the coverage fund). Moreover, on 1 June, the FMSB issued
advice to the government to extend the macroprudential toolkit to include limits on LTV, DTI and
DSTI ratios.
Rapid RRE price growth in Austria, partly driven by cash buyers, together with the existing
significant overvaluation of RRE prices in Vienna, suggest that vulnerabilities in the collateral
stretch are rising rapidly. The policy stance regarding the collateral stretch is assessed to be
appropriate but may not be sufficient. As for the household stretch, legally based limits could be
more effective in preventing a build-up of vulnerabilities related to loosening lending standards.

105

See footnote 89: some caveats apply to the OeNB survey data.

106

See footnote 89: some caveats apply to the OeNB survey data.

107

These measures are part of the Austrian legislation. With regard to covered bonds (“Pfandbriefe”), under §10 and §11 of
the Hypothekenbankgesetz, only mortgages with an LTV of less than 60% may be used as collateral in covered bonds; in
the case of agricultural land, the LTV limit can be up to 66%. With regard to building loans/loans under a savings and loan
contract (“Bausparkredit”), under §10 of the Bausparkassengesetz, mortgages under this regime may not exceed an LTV of
80% (based on the market value). According to the FMA Directive (§ 13 Z. 3 VU-KAV), the insurance sector is bound by an
LTV limit of 60% if mortgage loans are eligible for the coverage funds.

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Banking stretch
Exposures of Austrian banks to RRE are relatively low: total mortgage loans as a percentage of
GDP stood at 28% in Q1 2016 in Austria compared with an EU average of 36%. The average risk
weights for Austrian IRB banks are 24% (the EU average is 16%). This makes the Austrian banking
sector relatively less vulnerable to potential shocks related to RRE and better capitalised and thus
better able to absorb potential losses. However, generally the capitalisation of Austrian banks is
lower than that of their EU peers. The CET1 ratio for Austrian banks was 12.8% in Q1 2016
compared with an EU average of 13.9%. However, it has increased by 1.2 p.p. in the course of the
year.
Austrian authorities have taken a range of measures to increase banking sector resilience: the
capital conservation buffer (2.5% when fully phased in in 2019), the O-SII buffer (between 1 and
2%, fully phased-in by end-2018) and the systemic risk buffer (up to 2% since January 2016) (see
Table AT.2).
Given the high risk weights and low exposures to RRE, as well as the prudential measures taken,
the policy stance for the banking stretch is deemed appropriate and sufficient.

Table AT.3
Additional information on instruments and data available to micro and macro supervisory
authorities – Austria
Do the macro and micro supervisory
authorities have the powers necessary to
implement/amend policy quickly and
effectively if/when required?

Policy tools such as limits on LTV, DTI and DSTI ratios are currently unavailable to the
Austrian authorities. However, the Austrian authorities have communicated informal
expectations to banks. 108
The Austrian Financial Market Stability Board issued advice to the Ministry of Finance to
extend the macroprudential toolkit to include borrower-based macroprudential instruments in
the field of real estate financing on 1 June 2016. 109

The OeNB has recently started collecting data on new loans and the corresponding lending
standards. However, there is still a lack of reliable data on lending standards in Austria, since
a number of caveats apply to these data: (1) they cover only a relatively small market share
Do the macro and micro supervisory
(about 20-25% of housing loans collateralised by residential real estate); (2) the sample size
authorities have the necessary data to monitor changes over time; and (3) the variance in the data between banks is quite large. Hence, the
the risks and the impact of policy measures?
data need to be interpreted carefully. Unfortunately, there is no regional breakdown of these
new loans (or of their stock), which makes it hard to confirm the hypotheses about the precise
nature of the risks. However, if the current RRE price growth were to continue in the rest of
the country (alongside the long-term growth in Vienna), this sort of information would anyway
be irrelevant for policymaking.

108

See footnote 92.

109

See footnote 94.

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Annex with charts
Chart AT.1
Residential real estate price dynamics and
sustainability analysis

Chart AT.2
Household indebtedness and housing loans

(percentage)

(percentage)

HP yoy growth Austria
HP overvaluation Austria
HP yoy growth Vienna
HP overvaluation Vienna

existing housing loans yoy growth (right axis)
new housing loans yoy growth (right axis)
HH indebtedness in % of GDP (left axis)

25

56

30

20

55

25

15

54

10

20

53
15

5

52

0

10
51

-5

0

49

-15
-20
Q1 2000

5

50

-10

Q1 2003

Q1 2006

Q1 2009

Q1 2012

Q1 2015

Source: OeNB.

48
01/10

07/11

01/13

07/14

-5
01/16

Source: OeNB.

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Chart AT.3
Lending standards on new loans – confidential OeNB survey
a) Loan-to-value ratio

b) Debt-to-income ratio

(percentage)

(percentage)

sample average median (left axis)
number of observations (right axis)

sample average median (left axis)
number of observations (right axis)

100

7
6 6 6 6 6 6

90

10

7
6 6 6 6 6 6

9
6

80

6
8

5 5 5 5 5 5
5

70

5 5 5 5 5 5
5

7

4 4

4 4 4 4 4 4 4

60

4

50 3 3 3 3 3 3

6

4

5
3

40
30

2

20

4

3
2

3

2

2
1

10

1
1

0

0
2011

2012

2013

2014

2015

0
2011

0
2012

2013

2014

2015

c) Debt service-to-income ratio
(percentage)
sample average median (left axis)
number of observations (right axis)
50

7
6 6 6 6 6 6

45

6
40

5 5 5 5 5 5
5

35
4 4 4 4 4 4 4
30

4

25
20

3
2

15

2

10
1
5
0
2011

0
2012

2013

2014

2015

Source: OeNB.
Note: Some caveats apply to the OeNB survey data: (1) it only covers a relatively small market share (about 20-25% of housing loans collateralised
by residential real estate); (2) its sample size changes over time; and (3) the variance in the data between banks is quite large. For this reason, the
results must be interpreted with care (see footnote 89).

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Chart AT.4
Foreign currency loans
(percent of total loans)

Chart AT.5
Variable rate loans
(percent of total loans)
Austria
euro area

Austria
euro area
35

100
90

30
25

80
70
60

20
50
15
10

40
30
20

5

10

0
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

0
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Sources: OeNB, Statistics Austria, ECB, and Eurostat.
Note: Figures for the euro area represent only interest rate expenses on
euro-denominated loans.

Sources: OeNB, Statistics Austria, ECB and Eurostat.
Note: Figures for the euro area represent only interest rate expenses on
euro-denominated loans.

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Belgium
Key points
The main RRE-related vulnerability in Belgium is related to the fast increase in overall household
indebtedness combined with significant groups of already highly indebted households, against the
background of a significant increase in RRE prices over the past few years. The trend of rising
household indebtedness that, to a large extent, has been caused by a continued rapid increase in
lending for house purchases (these loans increased annually by 8.1% in June 2016 and when
corrected for securitisation operations by 5.3%) (see Charts BE.1 and BE.2). Furthermore, microlevel data on the distribution of financial wealth as well as DSTI and LTV ratios suggest that there
are specific groups of households that could entail financial vulnerabilities in the event of an
adverse macroeconomic shock. For this reason, banks could suffer higher than expected losses if
RRE prices were to decrease, interest rates increase or unemployment increase. This vulnerability
could become more pronounced if the trend of rising household indebtedness continues.
The increase in household debt combined with sub-groups of households with high DSTI and LTV
ratios should, however, be seen in conjunction with different mitigating factors. These include the
fact that Belgian households in general have a relatively high ratio of financial assets to debt (see
Chart BE.3) and that mortgage loans are typically amortised with maturities below 25 years at
origination.
From 2012 until recently, lending standards appeared to have tightened (particularly through a
shortening of maturities), but data for 2015 suggest that the tightening of lending standards has
come to an end recently as the share of new mortgage loans with DSTI ratios above 50% and LTV
ratios above 90% increased slightly for the first time since 2011. Also, the share of new mortgage
loans with DSTI ratios above 50% is still around 20%. This should, however, be seen in relation to
the decrease in maturities on newly issued loans. RRE prices have increased significantly over the
past 30 years and have been increasing faster than incomes or rents in recent years.
Finally, banks using IRB models to estimate risk weights for mortgage lending tend to have quite
low risk weights, standing at 10%, which could exacerbate the issue if there are higher than
expected losses in the event of an adverse macroeconomic shock. Policy measures taken by the
Nationale Bank van België/Banque Nationale de Belgique (NBB/BNB) include an add-on of 5 p.p.
to mortgage loan risk weights estimated by Belgian banks using IRB models, as well as a
communication calling for increased vigilance from the financial sector. The macroprudential addon introduced in December 2013 effectively raised the average risk weight for domestic mortgage
loan exposures of IRB banks from 10% to 15%. On the occasion of the publication, in June 2016, of
the Belgian Financial Stability Report (FSR), which also included a thematic article on the Belgian
mortgage market, the NBB/BNB announced its intention to take a new macroprudential measure
with regard to the Belgian IRB mortgage loan portfolios. The measure aims to build an additional
macroprudential capital buffer by increasing the LGD floors from 10% to 20% for loans with an
indexed LTV (ILTV) ratio above 80% and to 30% for loans with an ILTV ratio above 90%, based on
a harmonised ILTV measure. Hence, the measure aims to further increase resilience, while
discouraging the production of new loans with LTV ratios higher than 80%.
Overall, the Belgian authorities have focused on ensuring banks’ resilience to risks stemming from
the RRE sector. The decision of the NBB/BNB in December 2013 to impose an add-on to the
capital adequacy requirements for mortgage exposures of banks using internal ratings-based
models, as well as public communications from the NBB/BNB calling for increased vigilance with
regard to risks from residential real estate, may also serve to reduce the existing vulnerabilities.
Moreover, the tax deductibility of mortgage loans is being tightened. The NBB/BNB’s public

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commitment to take additional capital measures to target high-risk loans (e.g. those with a high
loan-to-value ratio) if they continue to constitute a significant share of the new loans issued is also
expected to limit, to some extent, a further build-up of vulnerabilities in the future. However,
measures directly addressing the vulnerabilities related to highly indebted households (the groups
of households with high DSTI and LTV loans) or the continued increase in RRE prices have not
been adopted. While the policy measures that have been implemented are appropriate given the
nature of RRE vulnerabilities in Belgium, they may not be sufficient to fully address them.

Table BE.1
Summary assessment – Belgium
Summary RRE risk
assessment narrative

Key risks are related to the banking, collateral and household stretches
The main RRE-related vulnerability in Belgium is related to the fast increase in overall household indebtedness,
combined with significant groups of already highly indebted households, against the background of a significant
increase in RRE prices over the past few years. Lending for house purchases has been rapidly increasing, with an
annual increase of 8.1% in June 2016 (5.3% when corrected for securitisation operations).
At the same time, groups of households are highly indebted, with high DSTI ratios including for new loans (more
than 20% of loans have a DSTI ratio at origination above 50% and almost 20% of new loans have a DSTI above
50%, and one-third of loans have LTV ratios above 90%).
RRE prices have increased significantly over the past 30 years (a 4% increase in 2015) and have been increasing
faster than incomes or rents in recent years. In nominal terms, RRE prices are now close to their level prior to the
financial crisis. There are some signs of price overvaluation, but alternative valuation models do not demonstrate
this unequivocally.
There are low risk weights (10%) for mortgage loans of banks using IRB models (before the 5 p.p. add-on).

Policy assessment given
risks

The policy stance is appropriate but not expected to be sufficient for the collateral and household
stretches
Measures directly addressing the vulnerabilities related to highly indebted households or the continued increase in
RRE prices have not been adopted.
Furthermore, the trend of tightening lending standards appears to have ended, which – together with very high
credit growth – indicates that vulnerabilities could be building up.
The add-on of 5 p.p. to risk weights is deemed sufficient to address the banking system stretch.
While the policy measures that have been implemented are appropriate given the nature of RRE vulnerabilities in
Belgium, they may not be sufficient to fully address them.

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Table BE.2
Summary of risks and policy measures – Belgium

Household stretch

Collateral stretch

Banking stretch

Summary risk
assessment/main risks

Debt is increasing rapidly and
groups of households have high
debt levels (in terms of both stocks
and flows).

RRE prices have increased
significantly over the past 30 years
(an increase of 4% in 2015). In
nominal terms, RRE prices are
now close to the level they had
prior to the financial crisis.
There are sub-groups of
households with high LTV ratios (in
both stocks and flows).

There are low risk weights on
mortgage loans of banks using IRB
models (before the risk weight
add-on).
The capitalisation of the Belgian
banking sector is increasing and
above the EU average (the
average for Belgium was 14.8% in
Q1 2016 against an EU average of
13.9%).
There has been a considerable
increase in lending for house
purchases.

Summary of policy measures
(implemented, planned, under
consideration)

Several communications on risks
starting with the 2012 FSR. The
monitoring of risks led to the
adoption of a microprudential
measure: self-assessment of the
degree of compliance with the EBA
opinion on good practices by
banks.

Several communications on risks
starting with the 2012 FSR. The
monitoring of risks led to the
adoption of a microprudential
measure: self-assessment of the
degree of compliance with the EBA
opinion on good practices by
banks.

Several communications on risks
starting with the 2012 FSR. The
monitoring of risks led to the
adoption of a microprudential
measure: a horizontal assessment
of the IRB models.

A tightening of tax deductibility
related to mortgage loans.

Add-on of 5 p.p. to risk weights for
mortgage loans of banks using IRB
models in 2014.
Phasing-in of the O-SII buffer of
0.75-1.5% from 1 January 2016
Countercyclical capital buffer at
0% from January 2016.

Assessment of policy
measures

Appropriate but not expected to
be sufficient

Appropriate but not expected to
be sufficient

Appropriate and expected to be
sufficient

Household stretch
The main vulnerabilities in the household stretch relate to a significant increase in the level of debt
and the groups of highly indebted households. In June 2016 lending for house purchases increased
by 8.1% year-on-year (by 5.3% when corrected for securitisation operations) (see Chart BE.1) and
the DTI ratio increased to 103% in Q1 2016 (see Chart BE.2). A general increase in the DSTI ratio,
as well as the share of loans with high DSTI ratios, is also worth noting. According to data from the
NBB/BNB, the share of loans with a DSTI ratio at origination above 50% was around 20% in
Belgium in 2015. Furthermore, one-third of outstanding loans have LTV ratios at origination above
90%. However, there are a number of mitigating factors, including limits on interest rate variability
and mortgage loans typically being amortised with maturities of or below 25 years at origination.
The NBB/BNB has addressed the identified vulnerabilities by means of communication (e.g. in its
2012 FSR) as well as by requiring banks to self-assess their compliance with the EBA opinion on
good practices.
Overall, these measures appear to have had an effect as credit conditions have generally tightened
since 2012, particularly with respect to the maturity at origination of mortgage loans. However, as
mentioned, the stock of loans with high DSTI ratios at origination is still high and new loans with a
DSTI ratio above 50% still constitute a sizeable share of new mortgages (almost 20%). Moreover,
data for 2015 suggest that the tightening of lending standards has come to an end recently, as the
share of new mortgage loans with DSTI ratios above 50% and LTV ratios above 90% increased
slightly for the first time since 2011 – despite interest rates continuing to be at low levels. However,
there are some factors that should be kept in mind. First, the shortening of loan maturities, which is

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a mitigating factor in this context, would tend to increase the DSTI ratios. Second, the large number
of refinancings recently could bias the data, although it is not clear in which direction.
Given the continued presence of risky groups of households in both the stock and flow of lending,
combined with a household debt level that has been generally increasing, rapid credit growth and
the halt in the tightening of lending standards, the current policy stance may not be sufficient to
contain the rising vulnerabilities in the household stretch. Measures directly addressing the
vulnerabilities related to highly indebted households have not been adopted. For these reasons, the
policy stance of Belgium is deemed appropriate but may not be sufficient. Furthermore, the
implementation of borrower-based measures, such as DSTI and LTV ratios, is the competence of
the Federal Government (but based on advice from the NBB/BNB).

Collateral stretch
Vulnerabilities in the collateral stretch are related to the significant increase in RRE prices over the
last 30 years – with only a minor correction in prices during the financial crisis – combined with a
considerable increase in household debt, particularly mortgage debt. In Q1 2016 RRE prices
increased by 2.3% annually and at a faster pace than income (the PTI index at the same time was
127% or 13 p.p. higher than one year ago) or rental prices (the PTR index at the same time was
102% or 3 p.p. higher than one year ago). Since 2010 the PTI and PTR indices in Belgium have
increased faster than the euro area average: at the end of 2015 they were, respectively, 10 p.p.
and 9 p.p. higher than the euro area average. Thus, the growth of RRE prices has exceeded the
growth of fundamentals, at least recently. The ECB real estate valuation methods suggest that RRE
prices are overvalued in Belgium (using the income-based model overvaluation is 31%, but another
model suggests an overvaluation of only 4%). However, overvaluation metrics are surrounded with
some uncertainty and are quite model-dependent, so some caution should be exercised when
looking at overvaluation figures. According to a model used by the NBB/BNB, RRE prices appear to
be only slightly overvalued.
In addition, as highlighted for the household stretch, groups of households with high LTV ratios in
the stock and flow of lending are present (one-third of outstanding and new loans have LTV ratios
at origination above 90%), which could give rise to losses in the financial sector in the event of
negative shocks to the economy. However, according to the slightly outdated 2010 Eurosystem
Household Finance and Consumption Survey, the share of high LTV loans in Belgium was lower
than in the euro area in general. Another mitigating factor is a generally high level of (liquid)
financial net wealth in relation to debt (see Chart BE.3), which increases households’ resilience to
negative shocks to the economy in general.
The NBB/BNB has addressed the identified vulnerabilities by means of communication (e.g. in their
2012 FSR) as well as by requiring banks to self-assess their compliance with the EBA opinion on
good practices. The rules for tax deductibility of mortgage loans have also been changed, which, all
else equal, should have put downward pressure on prices according to the NBB/BNB.
In January 2016 a high-level expert group established on the initiative of the Belgian Minister of
Finance suggested that an LTV cap should be introduced in Belgium. The group suggested that it
should initially be set at 100%, but that over time it would be reduced to e.g. 85% with certain
groups being allowed to breach the cap. Currently, measures in this area are the competence of
the Federal Government.
Overall, given the RRE price dynamics (i.e. a significant increase in RRE prices over the last 30
years almost without any correction in prices) and a possible overvaluation of RRE prices, in

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combination with increasing household debt as well as the halt in the tightening of lending
standards, the current policy stance is appropriate but may not be sufficient to contain the rising
vulnerabilities in the collateral stretch. Measures directly addressing the vulnerabilities related to the
continued increase in RRE prices have not been adopted.

Banking stretch
Overall, the Belgian banking sector’s solvency position is improving (in Q1 2016 the CET1 ratio
stood at 14.8%) and exceeds the EU average (13.9%). The loan-to-deposit ratio (88%) is lower
than the EU average (96%). Overall, the liquidity position of Belgian banks has improved in 2015 as
they became more reliant on customer deposits and less on the interbank market. The proportion of
market funding decreased and the coverage of liquid assets with short-term liabilities picked up
slightly.
The Belgian banking sector has a relatively high exposure to real estate loans (mortgages and
loans for construction and to real estate companies), which at the end of 2015 constituted 44% of
the total loan portfolio, increasing by 1 p.p. over the year. The corresponding ratio for the euro area
at the end of 2015 was 38%, decreasing by 0.4 p.p. over the year. In comparison to other EU
countries, the non-performing exposures in Belgium seem to be modest and have decreased
slightly.
Analyses by the NBB/BNB indicate that banks using IRB models to calculate risk weights generally
apply quite low risk weights to mortgage loans. On average, their risk weights for mortgage loans
(excluding the 5 p.p. add-on) are 10% compared with an EU average of 16%. One explanation for
the low risk weights is the historical absence of major drops in RRE prices or episodes of high
defaults on mortgage loans in Belgium; this influences banks’ computation of risk weights, since
they base their estimation on a sample period characterised by no major negative real estate
developments. In January 2016, the NBB/BNB made an official request to extend their risk weight
110
add-on policy measure for an additional year and on 18 February 2016 the ESRB assessed the
extension of the 5 p.p. add-on to the risk weights for Belgian banks’ mortgage loan exposures as
justified, suitable, proportionate, effective and efficient. The add-on applies to risk weights for
mortgage lending of banks using IRB models and it implies a total buffer of €2.8 billion to cover
losses in the RRE market (compared with current yearly losses that oscillate around €170 million).
Since the Belgian authorities have taken measures to address the low risk weights of the IRB
banks, the policy stance for the banking stretch is deemed appropriate and sufficient.

110

This is required since the NBB/BNB used Article 458 of the CRR to apply the risk weight add-on.

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Table BE.3
Additional information on instruments and data available to micro and macro supervisory
authorities – Belgium
Do the macro and micro supervisory
authorities have the powers necessary to
implement/amend policy quickly and
effectively if/when required?

The NBB/BNB has the power to exercise any prerogatives, including issuing
recommendations to the credit institutions at any time, within the scope of its competences. It
does not require any approval from other authorities in this respect. However, in view of
shared competences with the ECB with respect to macroprudential policy, the NBB/BNB will
inform the ECB about the main communications and recommendations.
The effective implementation of quantitative measures, such as caps on the LTV ratio, the
DSTI ratio, etc., is the competence of the Federal Government (but based on advice from the
NBB/BNB).
The procedure foreseen in Article 458 of the CRR (under which the risk weight add-on is
implemented) is rather long and complex as e.g. the assessment of different authorities (the
ESRB, the EBA and the European Commission) is needed. As a result, the NBB/BNB does
not consider that it could act in a quick and effective manner if additional measures would
need to be implemented under Article 458 or the current measure would need to be revised.
The NBB/BNB as a macroprudential authority can decide at any time to increase the
frequency and intensity of the monitoring of banks’ lending standards. In addition, the
NBB/BNB Organic Law (Article 36/33) explicitly foresees the possibility for the NBB/BNB to
request any information which is relevant for the exercise of its tasks.

Do the macro and micro supervisory
Currently, the NBB/BNB’s Executive Board monitors the Belgian RRE market every six
authorities have the necessary data to monitor months on the basis of e.g.:
the risks and the impact of policy measures?
a) data collected on banks’ lending standards at origination;
b)the risk profile and the quality of portfolios.
In addition, the NBB/BNB can at any time decide to increase the frequency and intensity of
the monitoring of banks’ lending standards.
One minor data-related issue relates to the refinancing of mortgage loans (which was quite
pronounced during the second half of 2014 and in 2015) as this tends to blur the picture
somewhat when monitoring lending standards.

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Annex with charts
Chart BE.1
Lending for house purchase in Belgium

Chart BE.2
Household debt-to-disposable income ratio

(EUR billions)

(percentage)

140

120

120

100

100
80

80
60

60
40

40
20

20

0
1998 2000 2002 2004 2006 2008 2010 2012 2014 2016

0
2000

2002

2004

2006

2008

2010

2012

2014

Source: ECB Statistical Data Warehouse.
Note: The chart shows Belgian banks’ mortgage loans, taking into
account (retained) securitisations of mortgage loans.

Source: ECB SDW.

Chart BE.3
Household debt-to-household total assets
ratio

Chart BE.4
House price developments in Belgium

(percentage)

(index: 2010 = 100)

25

120

20

110

15

100

10

90

5

80

0
1999

2001

2003

2005

2007

2009

2011

2013

2015

Source: ECB SDW.

70
2005

2007

2009

2011

2013

2016

2015

Source: Eurostat.

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Chart BE.5
Debt service ratio
(percentage)
8
7
6
5
4
3
2
1
0
1999

2001

2003

2005

2007

2009

2011

2013

2015

Source: Bank for International Settlements.

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Denmark
Key points
Vulnerabilities for Denmark are primarily related to the robustly increasing RRE prices – in
particular in the major cities – in combination with highly indebted households. Despite moderate
credit developments and although some of the risk indicators are moving in the right direction, RRE
prices are rising fast and are approaching pre-crisis levels (see Charts DK.7 and DK.8), in particular
in the major cities. In the Copenhagen area, the rate of price increase has been very high for some
time (in Q1 2016 house prices increased annually by 10.4% in Copenhagen and by 3.5% in the
whole of Denmark). The developments in the real estate market are fuelled by a number of
structural factors, such as a highly regulated rental market and a procyclical housing tax system. A
number of these structural factors together with high RRE prices are also encouraging a high debt
level. Aggregate data show that the Danish DTI ratio, at 263%, is among the highest in the world
(see Chart DK.1). Micro data also show that approximately 25% of homeowners have a DTI ratio
before tax above 300%, and 30% of homeowners have total debt relative to the value of their home
above 100%.
Some studies estimate that the vast majority of Danish households with high debt levels are
111
financially robust even in stressed scenarios. However, studies also find a strong negative
relationship between households’ debt levels and changes in their consumption during stressed
112
periods through both income and wealth effects. So, the direct credit risk seems limited for
Danish banks, but the high household indebtedness may lead to considerable negative effects for
the real economy with potential negative second-round effects on the Danish financial sector in the
event of an adverse scenario materialising such as a rise in interest rates, higher unemployment or
a fall in RRE prices. Moreover, a high proportion of interest-only loans means that this risk will
persist in the foreseeable future.
In order to address these risks, the Danish national authorities have introduced an LTV limit of
95%, published guidelines for banks and mortgage credit institutions to ensure caution in lending,
113
introduced a “supervisory diamond” for mortgage credit institutions that will come into force in
2018-20, and are gradually reducing mortgage interest tax deductibility.
While the policy measures taken are appropriate given the nature of the RRE vulnerabilities in
Denmark, they may not be sufficient to fully address them. Even though mortgage lenders have
themselves reported a tightening in lending standards, this has not yet had a noticeable impact on
the level of household indebtedness or real estate prices – on the contrary, both credit and prices
are still increasing in the major cities. In the light of the RRE price increases, particularly in the main
cities, there is a risk that these developments could lead to a further increase in household
indebtedness. Moreover, the high level of household debt is not expected to significantly decline
114
since it is not directly addressed by these policies. It is important to note that this assessment

111

See, for example, Andersen, A., Christensen, A., Nielsen, N., Koob, S., Oksbjerg, M. and Kaarup, R., “The Wealth and
Debt of Danish Families”, Monetary Review, Danmarks Nationalbank, Q2 2012.

112

See, for example, Andersen, Duus and Jensen (2014) as above fn. 76.

113

The “supervisory diamond” sets out a number of benchmarks that the Danish FSA generally considers to indicate mortgage
credit activities that have a higher risk profile. It consists of five indicators with corresponding limits: large exposures;
lending growth; interest rate risk of the borrower; interest-only lending; and short-term funding.

114

The LTV limit only affects new loans, while the supervisory diamond and the seven best practices for lending are a mix of
flow and stock measures. The change in mortgage interest tax deductibility will not be fully phased in before 2020 and the
supervisory diamond will not be fully implemented before 2020.

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reflects the fact that some of the measures have only been in effect for a limited period of time and
are entering into force gradually, while some of them only affect new borrowers.

Table DK.1
Summary assessment – Denmark
Summary RRE risk
assessment narrative

Key risks are related to the collateral and household stretches
The main vulnerabilities are considered to be the robustly increasing RRE prices – in particular in the major cities –
in combination with highly indebted households. In addition, if risks were to materialise, there could be potential
spillover effects on other countries in the Nordic-Baltic region.
Households’ debt levels are very high both relative to income (the average DTI ratio is 263%) and to GDP (123%).
Debt is particularly high for some households (25% of homeowners have DTIs above 300% and 30% of
homeowners have total debt of more than 100% of the value of their house).
RRE prices are increasing, driven by fast increases in major cities where they are approaching pre-crisis levels
(house prices increased annually by 3.5% in the whole of Denmark in Q1 2016 and by 10.4% in Copenhagen).
Even though the overall credit growth does not appear to be fast, mortgage credit institutions are increasing lending
in the major cities, which is coupled with rapid price increases.
High proportion of interest-only loans (50%) and variable rate loans (60%).

Policy assessment given
risks

The policy stance is appropriate but not expected to be sufficient for the collateral and household
stretches
While the policy measures taken are appropriate given the nature of the RRE vulnerabilities in Denmark, they may
not be sufficient to fully address them. Even though mortgage lenders have themselves reported a tightening in
lending standards, this has not yet had a noticeable impact on the level of household indebtedness or real estate
prices – on the contrary, both credit and prices are still increasing in the major cities. In the light of the RRE price
increases, particularly in the main cities, there is a risk that these developments could lead to a further increase in
household indebtedness.
Moreover, the high level of household debt is not expected to significantly decline since it is not directly addressed
by these policies. It is important to note that this assessment reflects the fact that some of the measures have only
been in effect for a limited period of time and are entering into force gradually, while some of them only affect new
borrowers.
Vulnerabilities related to the high proportion of interest-only loans and variable rate loans seem to be sufficiently
addressed by microprudential regulation.

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Table DK.2
Summary of risks and policy measures – Denmark
Household stretch

Collateral stretch

Banking stretch

Summary risk assessment/main
risks

Elevated indirect risks to financial
stability are regarded as the main
risk. The debt levels are very high
(the average DTI ratio is 263%),
even if lending standards appear to
have tightened. Around 25% of
households have DTIs above
300%. Some studies estimate that
the vast majority of Danish
households with high debt levels
are financially robust even in
stressed scenarios. However,
studies also find a strong negative
relationship between households’
debt levels and changes in their
consumption during stressed
periods through both income and
wealth effects. A high proportion of
interest-only loans means that this
risk will persist in the foreseeable
future.

The growth in RRE prices
increases the likelihood and
magnitude of any future price fall,
which, combined with the high
levels of indebtedness, could leave
a number of households in a
situation where the value of their
assets is below the value of their
debt. Currently, for 30% of
homeowners, the debt level is
above the value of their home. This
means that consumption could be
cut back in the event that an
adverse scenario materialises.
Moreover, the high debt levels may
also affect mobility in the housing
market if prices fall. However, RRE
prices are not deemed to be
overvalued at present, and the PTI
ratio is not high from a historical
perspective (see Chart DK.5).

Second-round effects are regarded
as the main risk, but bank resilience
is deemed high at present. The
high household indebtedness may
lead to an increase in banks’ NPLs
(e.g. from loans to corporates in the
retail or construction sectors).
Stress tests show, however, that
banks would withstand a severe
adverse scenario. But a potential
housing market shock could have a
broader impact on the financial
sector beyond banks.

Summary of policy measures
(implemented, planned, under
consideration)

7 best practices for lending (2015)

LTV limit of 95% (2015)

Supervisory diamond (2018 and
2020)

Supervisory diamond (2018 and
2020)

Supervisory diamond (2018 and
2020)

Gradual reduction in tax
deductibility (2012): reduced to
25.5% in 2019 for interest
payments above DKK 50,000 per
person (DKK 100,000 for couples);
for payments below this limit the tax
deductibility will be 33%

Systemic risk buffer at 0.2-0.6% in
2015 and 1-3% in 2019
Capital conservation buffer of
0.625% in 2016 and 2.5% in 2019
Countercyclical capital buffer at 0%
since January 2015

30-year maturity restriction on
mortgages (1990)
Assessment of policy measures

Appropriate but not expected to
be sufficient

Appropriate but not expected to
be sufficient

Appropriate and expected to be
sufficient

Household stretch
In Denmark, the main risk associated with residential real estate is related to the household stretch.
This is mainly due to high household indebtedness, both at the aggregate level and at the
household level (the household debt-to-GDP ratio is 123% and the average DTI ratio is 263%).
Looking at developments in the DTI ratio, it shows an improving trend since 2009 (the time series is
volatile and the latest data point shows an increase; see Chart DK.1). In addition, groups of highly
indebted households exist; approximately 25% of homeowners have a DTI ratio before tax above
300% (see Chart DK.3). Furthermore, 75% of families with high debt ratios have variable rate
mortgage loans, making them vulnerable to rises in the interest rate. In the aggregate, the shares of
interest-only loans (50%) and variable rate mortgages (60%) are also high. However, vulnerabilities
related to interest-only loans and variable rate mortgages are expected to be sufficiently addressed
by microprudential regulation. Moreover, some of the indicators are moving in the right direction.
For example, credit growth is currently modest and the credit gap is negative (see Chart DK.6). The
share of variable rate mortgage loans with an interest rate fixation of up to one year has also been
reduced from approximately 39% to 31% from 2014 to 2015. In the same period, the share of nonamortising mortgage loans fell from approximately 55% to 51%. This development is encouraging,
but indebtedness is still high in the household sector and vulnerabilities are expected to stay
elevated in the years ahead.

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Risks related to the household stretch are primarily of an indirect nature. Structural and institutional
features in Denmark (full recourse loans, personal bankruptcy legislation, beneficial social safety
nets, high pension assets and net wealth, etc.) limit credit risk for banks. Furthermore, because of a
well-developed financial system, for many years Danish households have had relatively easy
access to mortgage credit and it has been inexpensive to borrow against wealth, mainly due to a
115
large covered bond market subject to a “balance principle”. At the same time, Danish households
have very large pension wealth, which reduces their need to be debt-free when they retire. Some
studies estimate that the vast majority of Danish households with high debt levels are financially
116
robust even in stressed scenarios. However, studies also find a strong negative relationship
between households’ debt levels and changes in their consumption during stressed periods through
117
both income and wealth effects. So, the direct credit risk seems limited for Danish banks, but the
high household indebtedness may lead to considerable negative effects for the real economy, with
potential negative second-round effects on the Danish financial sector in the event of an adverse
scenario materialising, e.g. a rise in interest rates, higher unemployment or a fall in RRE prices.
Denmark is also one of the countries with first-hand experience that high debt levels in the
household sector may reduce private consumption in the aftermath of an adverse shock.
To address risks related to household stretch, both flow and stock measures have been taken by
Danish authorities. The FSA introduced in 2015 certain guidelines for mortgage banks and credit
institutions for their credit assessments. Moreover, the upcoming supervisory diamond, which will
be introduced in 2018 and 2020, will set numerical limits to be used in future prudential action in
five different areas. Four out of five of these measures are related to the stock of lending. In
addition to measures taken by the FSA, since 2012 there has also been a gradual reduction in
mortgage interest tax deductibility.
In Danmarks Nationalbank’s quarterly lending survey, banks and mortgage credit institutions report
that they have tightened their lending standards since Q4 2015 and that they expect to continue
tightening going forward. This tightening follows the introduction of the guidelines of the FSA and
the LTV limit. However, mortgage credit institutions continue to increase lending in the largest cities
(Copenhagen and Aarhus), where prices have been increasing. There is a risk that households’
indebtedness will continue to increase, together with increasing RRE prices in the urban areas.
The policy measures taken are appropriate to deal with vulnerabilities related to household stretch.
However, as regards the effectiveness of the measures, the evidence is mixed. On the one hand,
some risk indicators are improving and lending standards are tightening. On the other hand, the
overall household debt level is still very high in an international context and is not expected to
significantly decline since it is not directly addressed by these policies. Furthermore, the distribution
of debt shows that many households are still sensitive to adverse shocks (in particular in terms of
118
consumption). This suggests that vulnerabilities related to household indebtedness will persist. At
the same time, while overall credit developments are moderate, credit for house purchases is
increasing, together with RRE prices in the largest cities. Moreover, as mentioned above, some of
the measures taken are very recent, others only affect new borrowers and some of them are very

115

Meaning that there is matched funding between the bonds and the mortgage loans issued by mortgage credit institutions.

116

Andersen et al. (2012) see above fn. 111.

117

Andersen et al. (2014) see above fn. 76.

118

Stress tests carried out by Danmarks Nationalbank suggest that even indebted households are able to service their debt in
times of stress; however, the stress tests also suggest that there is a strong negative relationship between households’
level of indebtedness and the change in their consumption in stressed periods (see Andersen et al., 2014 as above fn. 76).

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gradual. Overall, due to these reasons, the policy stance is deemed to be appropriate but may not
be sufficient in addressing the vulnerabilities in the household stretch.

Collateral stretch
Risks related to the collateral stretch are elevated in Denmark. RRE prices are rapidly increasing,
particularly in the main cities, and are close to the pre-crisis peak (see Chart DK.7). The rapid
increases in RRE prices in urban areas imply that it is difficult for new households to enter the
housing market, and that they might be required to take on considerable mortgages to be able to
purchase a home. Thus, there is a risk that these developments would lead to a further increase in
household indebtedness. However, the price-to-income ratio has decreased by 0.7 p.p. between
Q1 2015 and Q1 2016. When looking at the debt-to-income ratio, approximately 30% of
homeowners have total debt relative to the value of their home above 100% (see Chart DK.4). High
average total debt relative to home value at loan origination for the median first-time buyers (96%),
in connection with the substantial fall in RRE prices in 2006-09, has left many Danish households
“underwater”. While the recent rise in RRE prices has restored households’ balance sheets
somewhat (see Chart DK.2), the proportion of households with high debt ratios remains at roughly
the same level as in 2009 (5%). The credit risk for banks and credit institutions is, however,
somewhat mitigated as households with high debt ratios also have assets other than their home to
draw on in case of financial problems. Therefore, the main identified risks related to collateral
stretch are of an indirect nature. For example, although RRE prices appear not to be overvalued at
present, a renewed fall in RRE prices could lead to reduced private consumption affecting
macroeconomic and financial stability. Falling RRE prices may also affect mobility in the housing
market, as highly leveraged households are typically less mobile due to low or negative housing
equity.
A number of structural factors are amplifying the vulnerabilities related to collateral stretch, e.g. a
highly regulated rental market as well as property value and land taxes which work in a procyclical
way. Housing tax in Denmark comprises a property value tax and a land tax. The property value tax
is capped at its 2002 level and there is a cap on the year-on-year increase in the land tax.
However, a number of mitigating factors are also in place, e.g. the low rate of home ownership and
a price elasticity of supply that appears to be high compared with other EU countries.
To address risks related to collateral stretch, the Danish authorities introduced an LTV limit of 95%
for new borrowers in November 2015. By building up buffers upfront, an LTV limit will work as a
cushion before losses reach banks’ balance sheets or before private consumption is scaled back. A
lower initial LTV for borrowers will also reduce the risk of households becoming underwater if RRE
prices fall. As mentioned earlier, the Danish banks report that they have tightened lending
standards partly due to this measure. Thus, the LTV limit is deemed to be appropriate to deal with
risks related to collateral stretch. However, given RRE price increases and the fact that the LTV
measure only affects new mortgages (meaning that households could finance their house
purchases with other types of loans) and is still quite generous compared with LTV limits in other
countries, the LTV limit may not to be sufficient to address vulnerabilities in the collateral stretch. It
should be noted that this policy measure has been in effect for only a short period of time, which
increases the difficulty of assessing its effectiveness. Overall, the policy stance for the collateral
stretch is deemed appropriate but may not be sufficient.

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Banking stretch
Although the mortgage and RRE markets are systemically important for the Danish financial sector,
there are not expected to be any immediate risks related to banking stretch. Stress tests indicate
that Danish banks would withstand a severe decline in private consumption and a fall in RRE
prices. Even if banks’ loan losses from the corporate sector were to increase as a result of reduced
private consumption, stress tests conducted by the IMF and national authorities show that the five
systemically important banks in Denmark would all have ample capital in relation to the minimum
requirements. However, it should also be noted that the interconnectedness between banks across
the Nordic-Baltic region implies that there could be significant cross-border spillovers between
banking systems from difficulties related to RRE stresses in any of the countries in the region. Also,
since the mortgage credit institutions have sold debt on to other investors, the potential housing
market shock could have a broader impact on the financial sector beyond banks.
In Q1 2016 the Danish banks had an average CET1 ratio of 15.7%, which is above the EU average
of 13.9%. The capital requirements for banks will increase as the various buffers are phased in;
both the capital conservation buffer and the systemic risk buffer will be fully phased in in 2019,
when their levels will reach 1.25% and 0.6-0.8%, respectively. The countercyclical capital buffer is
currently set at 0%. All systemic banks are already in compliance with the 2019 requirements.
Thus, the microprudential measures already in place are deemed to be appropriate and expected
to be sufficient to cover direct effects from RRE risks. Measures include the upcoming supervisory
diamond, which has certain limits regarding lending growth and short-term funding. At present,
these measures are deemed appropriate and expected to be sufficient to mitigate the risks.

Table DK.3
Additional information on instruments and data available to micro and macro supervisory
authorities – Denmark
Do the macro and micro supervisory
authorities have the powers necessary to
implement/amend policy quickly and
effectively if/when required?

The Systemic Risk Council has been set up in the aftermath of the latest crisis in Denmark. It
is composed of independent experts and representatives from various ministries,
Finanstilsynet (the Danish FSA) and Danmarks Nationalbank. The purpose of the Council is
to monitor and identify systemic financial risks and to issue observations, warnings and
recommendations to Finanstilsynet and, if they relate to legislation, to the government on how
to handle such risks. The Council has an advisory role only, hence recommendations are not
compulsory. If a recommendation is not complied with, the recipient must, however, explain
why within three months.

Do the macro and micro supervisory
The Danish authorities have access to very good household-level data on debt and assets.
authorities have the necessary data to monitor However, these data are only available with some lag. For example, data for 2014 will only be
the risks and the impact of policy measures?
available in the summer of 2016. Because of this lag, it is difficult for the Danish authorities to
follow the evolution of different risk indicators at the household level (DTI ratio, LTV ratio,
interest-only loans, etc.). This hinders the assessment of whether the measures taken by the
Danish authorities are having the intended consequences or not. However, from 2018-19 the
Danish authorities will have a credit register containing information on new lending, e.g. LTV,
DTI and LTI ratios on specific mortgage loans. This will allow close to real-time monitoring of
lending standards and should allow the authorities to study the impact of policy measures.

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Annex with charts
Chart DK.1
Household debt-to-income ratio

Chart DK.2
Housing wealth and household LTV ratio

(percentage of disposable income)

(left axis: DKK billions; right axis: %)
housing value (left axis)
LTV ratio (right axis)

350

3500

70

300

3250

65

250

3000

60

200

2750

55

150

2500

50

100

2250

45

50

2000

40

0
1973

1978

1983

1988

1993

1998

2003

2008

2013

1750
2003

35
2005

2007

2009

2011

2013

2015

Source: Danmarks Nationalbank.

Source: Danmarks Nationalbank.

Chart DK.3
Distribution of debt-to-income ratios for
mortgage borrowers in 2013

Chart DK.4
Distribution of total debt relative to the value
of the home for mortgage borrowers in 2013

(x-axis: DTI before tax; y-axis: percentage of homeowners)

(x-axis: total debt in relation to housing value; y-axis: percentage of
homeowners)
45

35

40
30
35
25

30

20

25
20

15

15
10
10
5

5
0

0
0-100

100-200

200-300

300-400

0-50

400-500 more than
500

Source: Danmarks Nationalbank.

50-100

100-150

more than 150

Source: Danmarks Nationalbank.

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Chart DK.5
House price-to-income gap
(left axis: index: 2000 = 1; right axis: percentage points)
price/income (left axis)
trend (left axis)
house price-to-income gap (right axis)
1.8

60

1.6

50

1.4

40

1.2

30

1.0

20

0.8

10

0.6

0

0.4

-10

0.2

-20

0.0
1975

-30
1980

1985

1990

1995

2000

2005

2010

2015

Source: Danmarks Nationalbank.

Chart DK.6
Credit-to-GDP gap
(left axis: percentage of GDP; right axis: percentage points)
credit-to-GDP (left axis)
trend (left axis)
credit-to-GDP gap (right axis)
300

80

250

60

200

40

150

20

100

0

50

-20

0
1970

-40
1975

1980

1985

1990

1995

2000

2005

2010

2015

Source: Danmarks Nationalbank.

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Chart DK.7
Residential real estate prices

Chart DK.8
Residential real estate prices

(index: January 2006 = 100)

(annual percentage change)

one-family houses
owner-occupied flats

one-family houses
owner-occupied flats

110

15
10

100

90

5
0
-5

80

-10
-15

70

-20
60
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Sources: Danmarks Nationalbank.

-25
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Sources: Danmarks Nationalbank.

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Estonia
Key points
Vulnerabilities related to residential real estate in Estonia are concentrated in the collateral stretch.
The major risk driver is increasing RRE prices, which are close to their all-time highest levels. Since
Q1 2009 nominal RRE prices have increased by 50% and real prices by 27%, and prices have now
reached just over 90% of pre-crisis levels. The rise in RRE prices has largely been driven by
household income growth, which has exceeded expected long-run productivity growth. This could
suggest that the income and RRE price growth might not be sustainable in the long run. In the
short-to-medium term, the identified main risk to financial stability is that the low interest rates and
continued growth in household income may increase imbalances in the RRE market. The latest
data, however, show some stabilisation in both nominal and real RRE prices over the past year.
Risks and vulnerabilities in the household and banking stretch categories appear more contained,
owing to relatively low indebtedness of the household sector, moderate growth in RRE lending and
high capital adequacy of the banking sector. The Estonian economy is, however, exposed to risks
in the global economy and the banking sector is structurally vulnerable due to its high degree of
concentration and interconnectedness, in particular with the Swedish banking system. International
risks could spill over to Estonia through both credit supply and trade channels.
The Estonian authorities have implemented a combination of precautionary policy measures to
prevent RRE lending standards from loosening from their current level and to increase the
resilience of the banking sector to structural vulnerabilities in the Estonian economy and financial
sector. As intended and expected, the LTV, DSTI and maturity limits have not significantly changed
the conditions on or volumes of new RRE lending over the past year. Should the risks around RRE
lending increase, Eesti Pank is able to tighten the requirements.
Overall, the macroprudential policy package is comprehensive and assessed to be appropriate and
expected to be sufficient in addressing the identified vulnerabilities related to RRE. Given the
comprehensive set of precautionary policy measures aimed at all three stretches, including
collateral stretch where the risks are assessed to be highest, the policy stance is assessed as
appropriate. Measures are also expected to be sufficient given the current level of and trend in
vulnerabilities: there is relatively low household indebtedness, mortgage growth is not rapid and the
banking sector is well capitalised should there be any shocks from the RRE sector. Nevertheless,
the policy stance is forward looking and the measures taken should reduce the misalignment of
incentives that could lead banks to issue an excessive number of mortgages in future or
households to take on an excessive amount of housing debt. Close monitoring of future
developments relating to RRE prices and conditions on and volumes of RRE lending is, however,
warranted. Furthermore, the predominance of variable rate housing loans exposes households to a
higher debt service burden in the long term.

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Table EE.1
Summary assessment – Estonia
Summary RRE risk
assessment narrative

Key RRE vulnerabilities are related to the collateral stretch
Rapidly increasing RRE prices that are close to their pre-crisis peak levels suggest that vulnerabilities are building
up in the collateral stretch (since Q1 2009 real property prices have increased by more than 50%). However,
recently, there appears to be some stabilisation in RRE prices.
Furthermore, RRE price increases have been supported by income growth which may not be sustainable in the
long run since it has outpaced productivity growth.
Risks and vulnerabilities in the household and banking stretches appear more contained, owing to relatively low
indebtedness of the household sector, moderate growth in RRE lending and high capital adequacy of the banking
sector.
The Estonian economy is, however, exposed to risks in the global economy and the banking sector is structurally
vulnerable due to its high degree of concentration and interconnectedness, in particular with the Swedish banking
system. International risks could spill over to Estonia through both credit supply and trade channels.

Policy assessment given
risks

The policy stance is appropriate and expected to be sufficient
The Estonian authorities have implemented a combination of precautionary policy measures to prevent RRE
lending standards from loosening from their current level and to increase the resilience of the banking sector to
structural vulnerabilities in the Estonian economy and financial sector.
Given the comprehensive set of precautionary policy measures aimed at all three stretches, the policy stance is
assessed as appropriate.
The measures are also expected to be sufficient given the current level of and trend in vulnerabilities.
Nevertheless, the policy stance is forward looking and the measures taken should reduce the misalignment of
incentives that could lead banks to issue an excessive number of mortgages in future or households to take on an
excessive amount of housing debt.

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Table EE.2
Summary of risks and policy measures – Estonia
Household stretch

Collateral stretch

Banking stretch

Summary risk assessment/main
risks

Currently, no major risks or
vulnerabilities are identified with
respect to household stretch.
Household debt-to-income and
leverage ratios (the latter measured
as debt over total financial assets)
have been decreasing over the past
three years and are currently
significantly below their recent
peaks.

Nominal and real RRE prices had
been rising since 2009, driven by
household income growth and
partly reflecting a recovery from the
preceding boom/bust cycle. The
latest data, however, show some
stabilisation in RRE prices over the
past year. The recent rise in income
and RRE prices has been
accompanied by only a moderate
increase in housing loans.
The combination of rising RRE
prices and increasing household
income entail a risk of
unsustainable developments in
RRE prices and lending that may
be further accelerated by the
current low interest rate
environment. In particular, the
recent rapid wage growth that has
been boosting RRE prices is
assessed to be inconsistent with
expected productivity growth in the
long term.

The banking sector is highly
concentrated and focused on
lending. The banking sector is also
highly interconnected with the
Nordic banking system, with the
risk of potential shocks spreading
from other countries to the Estonian
economy and financial system
through both credit supply and
trade channels.
In particular, the Estonian financial
system is dominated by large
Swedish-owned banks that are
exposed to a range of
vulnerabilities, e.g. in their home
RRE market and in wholesale
funding markets.

Summary of policy measures
(implemented, planned, under
consideration)

Finantsinspektsioon issued
guidelines on responsible lending
(December 2010)

Finantsinspektsioon issued
guidelines on responsible lending
(December 2010)

Finantsinspektsioon issued
guidelines on responsible lending
(December 2010)

Requirements for new housing
loans (as of 1 March 2015): at least
85% of new housing loans issued
per quarter must have:
a) a DSTI limit of 50% using either
the interest rate in the loan contract
plus 2 percentage points, or an
annual rate of 6%, whichever is
higher
b) maturity limit of 30 years

Requirements for new housing
loans (as of 1 March 2015): at least
85% of new housing loans issued
per quarter must have an LTV limit
of 85% (90% if guaranteed by
KredEx)

Systemic risk buffer requirement of
1% from 1 August 2016
O-SII buffer of 2% from 1 August
2016 for the two largest banks
Countercyclical capital buffer
(CCyB) requirement to be
maintained at 0%

From 2016 the limit on deductions
from taxable income was lowered
from €1,920 to €1,200 per taxpayer
Assessment of policy measures

Appropriate and sufficient

Appropriate and expected to be
sufficient

Appropriate and sufficient

Household stretch
The household stretch indicators do not signal any significant increase or a particularly high level of
vulnerabilities related to household indebtedness. The household debt-to-income ratio, at 72% in
Q4 2015, is significantly below its peak of 96%. In addition, the household leverage ratio (measured
as debt over financial assets) – at 37% – is also below its peak (see Chart EE.1). Both indicators
have been decreasing over the past three years, suggesting that vulnerabilities related to
household indebtedness are decreasing.
The policy measures implemented to prevent the household stretch include the debt service-toincome (DSTI) limit of 50% and the maturity limit of 30 years for new housing loans (set by Eesti
119
Pank as of 1 March 2015) , as well as guidelines on responsible lending (issued by
Finantsinspektsioon in December 2010). The DSTI ratio is calculated using either the interest rate

119

Up to 15% of housing loans issued each quarter are permitted to breach the requirements for new housing loans (LTV,
DSTI and maturity limits).

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in the loan contract (base rate plus margin) plus 2 percentage points, or an annual rate of 6%,
whichever is higher.
With regard to other policy measures, the maximum amount for the tax deductibility of interest
expenses on housing loans, training expenses, gifts and donations from taxable income was
reduced in 2016 (through changes in the Income Tax Act) from €1,920 to €1,200.
In light of the fact that the identified vulnerabilities related to household stretch are assessed to be
low and several appropriate policy measures have been taken, the policy stance is assessed to be
appropriate and sufficient for the household stretch.
Collateral stretch
Vulnerabilities related to residential real estate in Estonia are concentrated in the collateral stretch
category. Nominal and real RRE prices had been rising rapidly since 2009 (50% and 27%
respectively since Q1 2009; see Chart EE.2), driven largely by household income growth and partly
reflecting a recovery from the preceding boom/bust cycle. However, the RRE price-to-income ratio
has also been increasing (+9 p.p. over the last three years; see Table C.2 in Annex C), but less
than nominal and real RRE prices.
The main collateral stretch indicators signal rising vulnerabilities related to RRE prices over the past
three years, while the latest data show some stabilisation in RRE prices in the last year. Moreover,
both the PTI index at 109% and the PTR index at 78% have decreased considerably since their
previous peaks in Q2 2007 (181%) and Q4 2006 (104%), respectively. The ECB estimations of
potential overvaluation of RRE prices indicate that Estonian RRE prices are currently broadly in line
with fundamentals.
In the case of Estonia, a combination of rising RRE prices and increasing household income entails
a risk of unsustainable developments in RRE prices and lending that may be further accelerated by
the current low interest rate environment. In particular, the rapid rise in RRE prices has largely been
driven by household income growth, which has, however, exceeded expected long-run productivity
growth. This could suggest that the income and RRE price growth might not be sustainable in the
long run. In the short-to-medium term, the main identified risk to financial stability is that the low
interest rates and continued growth in household income may increase imbalances in the RRE
market. So far, the recent rise in income and RRE prices has been accompanied by only a
moderate increase in lending for house purchases, which in June 2016 increased by 4.6%
annually.
The policy measures implemented related to the collateral stretch include the loan-to-value (LTV)
limit on new housing loans (set by Eesti Pank as of 1 March 2015) and guidelines on responsible
lending (issued by Finantsinspektsioon). The LTV limit is 85% (90% for loans guaranteed by
KredEx). Currently, the LTV ratio is 69% for the stock of loans and 72% for new loans (see Table
C.1 in Annex C). Thus, for the average loan, this measure will be non-binding. However, it will
ensure that household indebtedness will not rise too far relative to the value of the collateral.
The RRE-related measures implemented have not had any major impact on the banking sector or
developments in the RRE market. The housing loan requirements were set close to the levels of
bank lending standards at the time and therefore, as intended and expected, they have not
significantly changed the conditions for housing loans or volumes of new housing lending (Eesti
Pank Financial Stability Review 2/2015). The past increase in RRE prices and household income
has also mitigated the effects of LTV and DSTI limits on borrowing.
While RRE prices were rising rapidly between 2009 and 2015 in Estonia, recovering from a
significant drop during the 2008 crisis, the data show some stabilisation in both nominal and real

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75

RRE prices over the past year. Moreover, the Estonian authorities have implemented a
combination of precautionary policy measures to prevent RRE lending standards from loosening
from their current level to curb the build-up of vulnerabilities going forward. Therefore, the policy
stance is assessed to be appropriate and expected to be sufficient for the collateral stretch.
Banking stretch
The capital adequacy of the Estonian banking sector is high, with a CET1 ratio at 34.8% in Q1
2016, and leverage is low (the assets-to-equity ratio was approximately 8% in June 2016 in
comparison with the EU average of 13%). Three banks, including the two largest, that participated
in the ECB’s comprehensive assessment and parent banks that participated in the 2016 EU-wide
stress tests were found to be very resilient in these exercises. There are, however, some structural
features that add to the vulnerability of the Estonian banking sector. These features may interact
with and be an amplifying factor for other vulnerabilities related to RRE.
Firstly, the banking sector is highly concentrated overall and particularly in lending. The Estonian
loan market is mostly divided between four large banks that in June 2016 covered 89% of the
market. Swedbank AS had the biggest market share (39% of the total loan portfolio). It was
followed by AS SEB Pank (23%), Nordea Bank AB Estonia Branch (19%) and Danske Bank A/S
Estonia Branch (8%). In December 2015 Eesti Pank concluded that the two largest banks,
Swedbank AS and AS SEB Pank, are to be considered as systemically important to the domestic
financial system.
Secondly, the banking sector is highly interconnected with the Nordic banking system, with the risk
of potential shocks spreading from other countries to the Estonian economy and financial system.
In particular, the Estonian financial system is dominated by large Nordic-owned banks which are
exposed to a range of risks – especially in their home RRE markets and in wholesale funding
markets – that could spill over to Estonia through credit supply and trade channels.
Currently, two banks (Swedbank and SEB Pank) are applying the internal ratings-based approach
in credit risk calculation within the capital adequacy framework. Based on the banking groups’
public financial statements in 2015, the average risk weight for RRE loans was 17% in Swedbank
and 12% in SEB Pank. All other banks use the standardised approach in which the risk weight for
RRE loans is 35%.
The policy measures implemented to prevent the banking stretch include the systemic risk buffer
requirement of 2% (set by Eesti Pank as of 1 August 2014), as well as guidelines on responsible
lending (issued by Finantsinspektsioon). The systemic risk buffer is intended to ensure the
resilience of the financial sector to structural (non-cyclical) vulnerabilities in the Estonian economy
and financial sector and to related non-cyclical risks that could have a serious negative impact on
the national financial system or the real economy. On 1 August 2016 the systemic risk buffer was
lowered to 1% and the O-SII buffer requirement of 2% was applied to the two largest banks.
Since Estonian banks are highly capitalised, not highly leveraged, have comparatively high risk
weights for RRE exposures, and have a number of capital buffers in place, the policy stance is
deemed appropriate and sufficient for the banking stretch.

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Table EE.3
Additional information on instruments and data available to micro and macro supervisory
authorities – Estonia
Do the macro and micro supervisory
authorities have the powers necessary to
implement/amend policy quickly and
effectively if/when required?

The macroprudential authority in Estonia is Eesti Pank.
The currently available macroprudential policy package is comprehensive.
Eesti Pank is able to tighten requirements for new housing loans, if necessary.
Eesti Pank is also able to reduce the risks from total credit growth by raising the
countercyclical capital buffer (CCyB) rate, if necessary.

Do the macro and micro supervisory
Eesti Pank has comprehensive data on conditions on new RRE lending (LTV ratio, DSTI ratio
authorities have the necessary data to monitor and maturity at loan origination).
the risks and the impact of policy measures?

Annex with charts
Chart EE.1
Household indebtedness

Chart EE.2
Real property prices

(percentage)

(index: Q1 2009 = 100)

debt-to-disposable income ratio (left axis)
debt-to-GDP ratio (left axis)
deposits and cash as a ratio to debt (left axis)
interest burden (right axis)

total real property
apartments
houses

120

7

100

6

120

100

5
80

80

4
60

60

3
40

40

2
20

0
2005

2007

2009

2011

2013

2015

Sources: Statistics Estonia and Eesti Pank.

1

20

0

0
2007

2009

2011

2013

2015

Sources: Statistics Estonia and Estonian Land Board.

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Finland
Key points
Finland has RRE vulnerabilities related to high and increasing household indebtedness, especially
among some groups of households. Households’ DTI ratio is relatively high at 112% (the EU
average for the 19 available countries is 106% and Finland has the sixth highest ratio). The
household debt-to-GDP ratio is relatively high at 66% (an EU average of 56%, with Finland having
the seventh highest ratio). Both ratios are currently at their historical peaks. The debt is
concentrated in certain households: according to the latest data, 26.5% of housing debt is borne by
households whose total debt is over four times higher than their annual monetary income. In
addition, 10% of households have DTI ratios above 300% and these households account for almost
half of total household debt. Moreover, households appear to be exposed to interest rate risks,
since more than 95% of new and existing mortgage loans have variable interest rates.
At the same time, the MFI sector has a large mortgage portfolio, coupled with high leverage. Risks
linked to the collateral stretch appear to be slightly more limited, with high nominal albeit flat RRE
prices. RRE price indicators, such as price-to-income and price-to-rent ratios, are close to their
long-run averages (see Chart FI.6), suggesting that there is no clear evidence of overvaluation in
RRE prices. Nevertheless, given the current weak economic outlook for the Finnish economy, there
could be a risk of decreasing RRE prices in the event of a negative economic shock.
An economic or financial shock could lead to the crystallisation of some of the above-mentioned
risks – for example, if unemployment increases and/or income growth decreases, then some highly
indebted households may find it more difficult to service their debts and the number of mortgage
defaults may increase, leading to direct credit losses for banks, especially if accompanied by a
decrease in RRE prices. Moreover, if an adverse economic scenario does materialise, the
associated negative household income and wealth effects may reinforce the initial shock,
amplifying the negative direct and indirect effects on financial stability (e.g. if households need to
reduce consumption in order to service their mortgage loans).
In relation to the identified vulnerabilities, a wide range of relevant macroprudential measures and
other policies have been implemented in Finland. Starting with fiscal measures impacting
borrowers’ incentives, mortgage interest tax subsidies are being gradually reduced every year from
the current 55% by 10 p.p. until they reach 25% in 2019 (until 2010, the share of mortgage interest
payments subject to tax relief was 100%). The Finanssivalvonta (the Finnish Financial Supervisory
Authority – FIN-FSA) has also published recommendations for banks regarding stressed loan
interest rates and the maximum maturity that banks should use in their credit assessments.
Targeting the adequacy of collateral, a 90% LTV limit (95% for first-time buyers) became binding
through a legislative amendment from July 2016 onwards. Moreover, in order to strengthen credit
institutions’ capital base, the capital conservation buffer (2.5%) was introduced in January 2015. OSII surcharge requirements (0.5-2.0%) were introduced for the most significant credit institutions as
of January 2016. In June 2016 the FIN-FSA Board decided to take measures to introduce a credit
institution-specific minimum level of 10% for the average risk weight on housing loans of credit
institutions that have adopted the IRB approach. The minimum level is set to come into force on 1
July 2017 at the latest. The contemplated means for setting the minimum level is via Article 458 of
the CRR. At the moment, the Finnish authorities do not have the legal powers to implement other
relevant macroprudential measures such as LTI, DTI and DSTI limits to deal with risks linked to
household stretch.
While the recently introduced LTV measure and the planned floor for IRB banks’ risk weights are
expected to indirectly contribute to a reduction of household stretch, macroprudential measures

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such as LTI, DTI or DSTI limits would be more effective in preventing a further rise in the number of
highly indebted households (it should also be noted that the introduced LTV measure will only
affect new borrowing). The gradual reduction of mortgage interest tax subsidies is an important
policy change impacting households’ incentives and working in the right direction.
While these policy measures are appropriate given the nature of RRE vulnerabilities in Finland,
they may not be sufficient to fully address them. However, it should be noted that the Finnish
authorities do not have the legal powers to implement other relevant macroprudential measures
such as limits on LTI, DTI or DSTI ratios, which could be used to curb further increases in
household indebtedness.

Table FI.1
Summary assessment – Finland
Summary RRE risk
assessment narrative

Key risks are related to the banking, collateral and household stretches
The main vulnerabilities are high and increasing household indebtedness, especially among some groups of
households. In addition, if risks were to materialise, there could be potential spillover effects on other countries in
the Nordic-Baltic region.
Households’ debt levels are relatively high in Finland: the DTI ratio is relatively high at 112% as is the debt-to-GDP
ratio at 66%.
More concerning are the groups of highly indebted households: 10% of households have DTI ratios above 300%
and these households account for almost half of total household debt.
In addition, households appear to be exposed to interest rate risks, since more than 95% of new and existing
mortgage loans have variable interest rates.
Price indicators suggest that prices relative to income and rents are close to their long-term average; however,
given the weak economic outlook, the likelihood of a manifestation of RRE risks over the short-to-medium term is
elevated.
The banking sector is concentrated with large exposures to RRE and is very interconnected with the Nordic
banking system and, to some extent, reliant on market funding. Also, the potential direct risks to the banking and
financial system could be significant if they were to materialise, especially given the size of the mortgage market in
relation to the banking system and the overall economy.

Policy assessment given
risks

The policy stance is not expected to be sufficient for the household stretch
While the measures taken are deemed appropriate and conceptually suitable given the nature of risks, it is not
clear that they will significantly mitigate vulnerabilities related to the household stretch (in particular, the high overall
indebtedness of households and the large share of highly indebted households).
The recently introduced LTV measure and the planned floor for IRB banks’ risk weights are expected to indirectly
contribute to a reduction of household stretch, but macroprudential measures such as LTI, DTI or DSTI limits would
be more effective in preventing a further rise in the number of highly indebted households (it should also be noted
that the introduced LTV measure will only affect new borrowing).
The situation is further complicated by the fact that the Finnish authorities lack the legal instruments to implement
certain measures such as LTI, DTI and DSTI limits, preventing them from directly addressing vulnerabilities in the
household stretch in the short-to-medium term.
On the other hand, the gradual reduction of mortgage interest tax subsidies is an important policy change
impacting households’ incentives and going in the right direction.
While these policy measures are expected to be sufficient for the collateral and banking stretches, they may not be
sufficient for the household stretch.

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Table FI.2
Summary of risks and policy measures – Finland
Household stretch

Collateral stretch

Banking stretch

Summary risk assessment/main
risks

Finland has RRE vulnerabilities
related to the high and increasing
household indebtedness.
Household debt seems relatively
high in Finland: the DTI ratio is
relatively high at 112%. The debtto-GDP ratio is also relatively high
at 66%. Some groups of
households in particular would be
particularly vulnerable to adverse
economic conditions or
developments in the RRE market.
10% of households have DTI ratios
above 300% and these households
account for almost half of total
household debt.
In addition, households appear to
be exposed to interest rate risks,
since more than 95% of new and
existing mortgage loans have
variable interest rates.

RRE price indicators, such as priceto-income and price-to-rent ratios,
are close to their long-run
averages, suggesting that there is
no clear evidence of overvaluation
in RRE prices. Nevertheless, given
the current weak outlook for the
Finnish economy, there could be a
risk of decreasing RRE prices in the
event of a negative economic
shock.

The potential direct risks to the
banking and financial system could
be significant if they were to
materialise, especially given the
size of the mortgage market in
relation to the banking system and
the overall economy.
The Finnish banking sector is
characterised by large exposures of
banks to residential real estate, a
high concentration, a significant
reliance on wholesale funding and
strong connections to the Nordic
banking system via foreign
ownership, which increases the risk
that housing market problems in
other Nordic countries could spread
to Finland’s financial system.

Summary of policy measures
(implemented, planned, under
consideration)

Tax deductibility is being gradually
reduced to 25% by 2019

LTV limit of 90% (95% for first-time
buyers) in effect since July 2016

Capital conservation buffer of 2.5%
since January 2015

Recommendation of the FIN-FSA
(2010) related to cautious mortgage
lending (ability to pay with an
interest rate of 6% and a maximum
maturity limit of 25 years; exercise
caution in granting loans with LTV
ratios higher than 90%)

O-SII buffer of 0.5-2% since
January 2016
Process initiated to introduce an
average risk weight floor of 10% for
IRB banks’ mortgage exposures
under Article 458 of the CRR

LTV limit of 90% (95% for first-time
buyers) in effect since July 2016
Assessment of policy measures

Appropriate but not expected to
be sufficient

Appropriate and expected to be
sufficient

Appropriate and expected to be
sufficient

Household stretch
Households in Finland are highly indebted. This is reflected in both the debt-to-disposable income
120
(DTI) ratio, which is relatively high at 112% (compared with an EU average of 106% for the 19
countries for which data are available, with Finland having the sixth highest ratio), and the
aggregate leverage ratio (measured as household debt over financial assets), which is high at
121
around 50% . The household debt-to-GDP ratio is also relatively high at 66% (compared with an
EU average of 56%, with Finland having the seventh highest ratio). The continued weak economic
developments in Finland have led to muted growth in households’ disposable income, while at the
same time households have continued to accumulate debt. As a consequence, the aggregate DTI
ratio has increased by 5.5 p.p. over three years and by 2.5 p.p. since last year, to 112.2% in Q1
2016.
While aggregate debt levels are high, debt is also very unevenly distributed among households.
Information on the distribution of housing debt indicates that debt is concentrated in a relatively
small group of the most indebted households. Moreover, households with large housing loans

120

According to the slightly outdated Eurosystem Household Finance and Consumption Survey, at the end of 2009 over 11%
of Finnish households had negative net wealth after all households’ assets and liabilities were taken into account.

121

However, this measure does not include earnings-related pension assets of Finnish households (around €180 billion at
end-2015). Therefore, when households’ leverage is measured using debt as a percentage of total financial assets, the
absence of these pension assets exaggerates Finnish indebtedness in an international comparison. Including assets held
by the Finnish employment pension schemes, the ratio would be significantly lower, at around 30%.

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usually also have a large debt burden in relation to their annual income. For example, according to
the latest data, 26.5% of housing debt is borne by households whose total debt is over four times
higher than their annual monetary income. Moreover, 10% of households have a debt-to-income
ratio above 300% and they account for half of total housing debt and almost half of total household
debt.
Credit dynamics in Finland are, however, less of a concern than the rise in household
indebtedness: loans for house purchases grew by 2.6% annually in May 2016. At the same time,
debt servicing costs for the Finnish households were the lowest among the group of focus
countries, standing at 7% of their income. Over the last three years, these costs have remained
more or less flat.
The low level of interest rates supports households’ financial position and the overall debt servicing
ability of households has remained good despite the weak economic outlook in Finland. Therefore,
direct credit risks to the banking sector are seen as limited at present. However, more than 95% of
new and existing mortgage loans have variable interest rates. This makes Finnish borrowers
sensitive to a potential increase in interest rates. However, the fact that Finnish households
typically amortise their loans on a monthly basis mitigates both the direct and indirect risks linked to
the high household indebtedness in Finland.
In order to address vulnerabilities linked to household stretch, the FIN-FSA issued
recommendations in 2010 for banks regarding the stress rate and amortisation rate they should use
in their credit assessments (ability to pay with an interest rate of 6% and a maximum maturity limit
of 25 years and to be cautious granting loans with LTV ratios higher than 90%). Moreover, the tax
deductibility of housing loan interest payments is being gradually reduced from 2011 when the paid
interests were fully subject to tax relief. In 2016, 55% of paid interests are subject to tax relief. The
government’s plan is to reduce the tax deductibility further by 10 percentage points per year for the
next four years. Thus, in 2019, only 25% of interest payments will be subject to the relief.
While the recently introduced LTV measure and the planned floor for IRB banks’ risk weights are
expected to indirectly contribute to a reduction of household stretch, macroprudential measures
such as LTI, DTI or DSTI limits would be more effective in preventing a further rise in the number of
highly indebted households (it should also be noted that the introduced LTV measure will only
affect new borrowing). The situation is further complicated by the fact that the Finnish authorities
lack the legal instruments to implement certain measures such as LTI, DTI and DSTI limits,
preventing them from directly addressing vulnerabilities in the household stretch in the short-tomedium term. However, the gradual reduction of mortgage interest tax subsidies is an important
policy change impacting households’ incentives and working in the right direction. While these
policy measures are appropriate given the nature of RRE vulnerabilities in Finland, they may not be
sufficient to fully address them.

Collateral stretch
Price indicators point to relatively stable RRE price developments in Finland. Both price-to-income
and price-to-rent ratios are close to their long-term averages (see Chart FI.6). Generally, RRE
prices are higher in growth centres than in the rest of the country. However, no significant
overvaluation of RRE prices has been detected, even if some indicators calculated by the ECB

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show that there may be slight overvaluation. Given the weak outlook for the Finnish economy
(Finnish economic growth is forecast to be the second lowest or lowest among EU countries in
122
2016-17 ), there is a risk of an RRE price correction due to e.g. an economic shock despite no
obvious overvaluation of RRE prices in Finland.
Furthermore, new housing loans have relatively high loan-to-value (LTV) ratios in Finland. Two
surveys conducted in 2010 and 2012 by the FIN-FSA show that the self-financing share has been
below 10% for a significant proportion (more than one-third) of new housing loans in the sample,
i.e. the LTV ratio was over 90% at loan origination. This means that a significant portion of new
borrowers are sensitive to a fall in RRE prices. The most recent survey (based on a sample
covering over 90% of all new mortgages in October 2014) showed that the average LTV ratio for
newly issued residential mortgages was 70.4%. However, given the amortisation of mortgages on a
monthly basis, the average LTV ratio for the stock of housing loans is considerably lower than that
for new housing loans (at loan origination). Based on data collected for the 2014 survey, the LTV
ratio for the total stock of mortgages was 58.2%.
The analysis of institutional and structural features of the RRE market in Finland suggests that
there are some factors that can mitigate negative shocks to RRE markets, such as the rather short
mortgage maturities as well as a positive net migration flow and the increasing number of
households supporting housing demand. However, some factors might amplify negative shocks to
RRE markets, such as the high share of mortgages with variable interest rates and the large share
of the construction sector in GDP.
In order to address vulnerabilities linked to the collateral stretch, a regulatory cap on the LTV ratio
was introduced in July 2016 through a legislative amendment. The limit was set at 90% for buyers
of real estate, while the limit for first-time buyers was set at 95%. According to the legislation, the
FIN-FSA may, on certain grounds, tighten the limit by 10 p.p. (down to 80% and 85%, respectively).
Given (i) muted RRE price dynamics, (ii) no obvious signs of overvaluation in RRE prices, (iii)
rather short mortgage maturities, (iv) a common practice of amortising mortgages on a monthly
basis, and (v) the prevailing levels of LTV ratios on new lending and in the mortgage stock (and in
particular the cap on the LTV ratio, but also the gradual removal of tax subsidies on mortgage
interest payments, which is also expected to positively contribute to correcting households’
incentives and thus the collateral stretch), the policy measures taken are deemed to be appropriate
and expected to be sufficient to address vulnerabilities related to the collateral stretch.

Banking stretch
The Finnish banking sector is characterised by large exposures to residential real estate, a high
concentration (overall and in housing, the three largest banks account for 80% of the loan stock), a
significant reliance on wholesale funding and strong connections to the Nordic banking system via
foreign ownership, which increase the risk that housing market problems in other Nordic countries
could spread to Finland’s financial system.

122

European Commission Spring 2016 Economic Forecast. The Finnish economy has nevertheless returned to growth after
three years of contraction.

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Banking stretch and resilience indicators also reveal that the Finnish MFI sector is highly leveraged
123
(total assets were 18 times capital and reserves at the end of Q2 2016) and dependent on RRE
lending as a source of income. However, in the past years, credit institutions in Finland have been
deleveraging (leverage has declined to 18 from 20 one year earlier and from 21 three years ago).
Credit for house purchases accounted for 44% of total credit to residents in Finland, which was well
above the EU average of 35% and lower only than in the UK, Slovakia and Sweden, all of which
are focus countries. Over the past year, the annual growth rate of the stock of housing loans stood
at 2-3%. In relation to GDP, the stock of housing loans has been stable (at 43-44%) since 2013.
Overall, capital adequacy ratios are high in the Finnish banking sector (see Chart FI.4). In Q1 2016
the CET1 ratio amounted to 21.1% and increased by 4.2 p.p. compared with the level a year
earlier. Banks’ non-performing assets arising from loans to households have remained low relative
to the loan stock. At the end of March 2016, banks’ non-performing loans to households totalled
around €1.1 billion, i.e. 0.9% of the stock of household loans.
In order to address vulnerabilities linked to the banking stretch, the capital conservation buffer
(2.5%) and the O-SII buffer (0.5-2.0%) are in force. In addition, as a planned measure, the FIN-FSA
decided to take measures to introduce a credit institution-specific minimum level of 10% for the
average risk weight on housing loans of credit institutions that have adopted the IRB approach. The
minimum level will come into force on 1 July 2017 at the latest. The basis for setting the minimum
level is Article 458 of the CRR.
Given the overall high solvency ratios of Finnish banks, and taking into account the planned and
already introduced policy measures related to RRE sector vulnerabilities, the policy stance related
to banking stretch is deemed appropriate and expected to be sufficient.

Table FI.3
Additional information on instruments and data available to micro and macro supervisory
authorities – Finland
Do the macro and micro supervisory
authorities have the powers necessary to
implement/amend policy quickly and
effectively if/when required?

The powers conferred on macroprudential supervisory authorities allow the possible
imposition of stricter national measures than those set out in the common EU regulatory
framework in order to address systemic risk. The Finnish authorities are not equipped with
powers to restrict the maximum size of new housing loans relative to the borrower’s debt
servicing capacity and loan maturities, or to impose loan amortisation requirements.

Do the macro and micro supervisory
Starting in H2 2016 the FIN-FSA will start collecting new data on housing loans, their LTV
authorities have the necessary data to monitor ratios and the value of collateral at loan origination.
the risks and the impact of policy measures?
In 2010 and 2012 the FIN-FSA conducted two sample surveys on LTV ratios of new housing
loans.

123

The MFI sector also includes some leveraged credit institutions that are not engaged in household lending in Finland (e.g.
branches of foreign credit institutions and a credit institution providing funding for the local public sector). The leverage ratio
is also affected by the concentration of the whole derivative position of Nordea Group in the balance sheet of Nordea Bank
Finland.

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Annex with charts
Chart FI.1
Households’ indebtedness

Chart FI.2
Housing loans: new drawdowns and
annual growth rate of the stock

(left axis: percentage; right axis: percentage points)

(left axis: percentage; right axis: EUR billions)

household credit, % of disposable income (left axis)
credit-to-GDP ratio, trend (left axis)*
deviation from trend (right axis)
household credit, % of GDP (left axis)

annual change in housing credit (left axis)
new drawdowns of housing loans (right axis)

140

15

20

30

120

10

15

25

5

10

20

0

5

15

-5

0

10

-10

-5

5

-15

-10
1990

100
80
60
40
20
0
1979

1984

1989

1994

1999

2004

2009

2014

0
1995

2000

2005

2010

2015

Sources: BIS, Statistics Finland and Suomen Pankki – Finlands Bank.
Notes: Household loan stock including household share of housing
company loans. (*) Calculated using a one-sided Hodrick-Prescott filter
(lambda 400,000).

Sources: Statistics Finland and Suomen Pankki – Finlands Bank.
Notes: In real terms (at consumer prices for the most recent 12 months).
New drawdowns are a 12-month moving sum.

Chart FI.3
Average interest rate on new drawdowns of
housing loans

Chart FI.4
Capital ratios for the banking sector

(percentage)

(percentage)
total capital adequacy ratio
tier 1 ratio
common equity tier 1 ratio

average interest rate on new housing loans
average reference rate on new housing loans
average margin on new housing loans
24

3.0

22

2.5
20

2.0
18

1.5
16

1.0

14

0.5

0.0
01/10

12

12/10

11/11

10/12

09/13

08/14

07/15

06/16

Source: Suomen Pankki – Finlands Bank.

10
2009

2010

2011

2012

2013

2014

2015

2016

Source: Finnish Financial Supervisory Authority.

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Chart FI.5
Households and their debt-to-monetary
income ratio

Chart FI.6
House price ratios

(index: 1981 = 100)

(percentage)

housing prices relative to consumer prices
housing prices relative to rents
average of the review period
housing prices relative to wage and salary earnings
average of the review period

proportion of households
proportion of household debt
proportion of housing debt

250

50
45

200

40
35

150

30
25

100

20
15

50

10
5
0
0%

over 0
100–
and up 200%
to 100%

200–
300%

300–
400%

over
500%

400–
500%

Sources: Statistics Finland and Suomen Pankki – Finlands Bank.
Note: The figures have been published in 2016 and pertain to the
situation in 2014.

0
1981

1986

1991

1996

2001

2006

2011

2016

Sources: Statistics Finland and Suomen Pankki – Finlands Bank.

Chart FI.7
Real house prices in different regions
(index: 2005 = 100)
whole country
greater Helsinki*
Finland excl. greater Helsinki
satellite municipalities**
130
120
110
100
90
80
70
60
50
2005

2007

2009

2011

2013

2015

Source: Statistics Finland.
Note: (*) Helsinki, Espoo, Vantaa, Kauniainen; (**) Hyvinkää, Järvenpää,
Kerava, Riihimäki, Kirkkonummi, Nurmijärvi, Sipoo, Tuusula, Vihti.

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Luxembourg
Key points
Residential real estate-related risks in Luxembourg relate to the combination of high RRE prices
and increasing household indebtedness. Prices are currently at an unprecedentedly high level
(based on available data), and are increasing both in relation to income and the level of rents (in Q1
2016 nominal prices rose by 4.5% annually, the PTI index increased by 6 p.p. annually and the
PTR index increased by 4 p.p. annually). These price developments have been sustained by a
structural imbalance between strong housing demand fuelled, inter alia, by demographic factors
and policy incentives and supply-side limitations on the availability of housing. ECB models suggest
some degree of overvaluation of residential property prices, which is confirmed – though to a
smaller extent – by the models of the Banque centrale du Luxembourg.
Vulnerabilities also exist for the household stretch, relating to a high and increasing level of debt.
The stock of loans for house purchases increased by 6% annually in June 2016 and the debt-todisposable income ratio appears high at 149% in Q1 2016. However, the debt-to-GDP ratio is more
moderate at 57% in Q1 2016. On average, the LTV and DSTI ratios in Luxembourg’s mortgage
market are robust and represent a mitigating factor. However, the distribution of the LTV and DSTI
ratios both for new and outstanding mortgages suggests that there is a notable share of loans with
124
high LTV and DSTI ratios. There are two different types of risks associated with this. First, while
the vulnerabilities in the household stretch are already elevated given the aggregate level of
household debt, there is a risk that the share of highly indebted households increases further with
the ongoing robust growth in RRE prices and housing loans. Second, in the event of unexpected
changes in the real estate market or the broader real economy (e.g. shocks to economic growth,
income or unemployment), the associated negative household income and wealth effects (e.g. if
households need to reduce consumption in order to service their mortgage loans) may reinforce the
initial shock, leading to deeper economic consequences as well as negative direct and indirect
effects on financial stability.
Mortgage debt is not concentrated in certain households; therefore, any income or interest rate
shock would be more widely distributed across the Luxembourg economy. A potential mitigating
factor is that the financial assets of Luxembourg households are also relatively high, thereby
limiting the possible impact of adverse developments if households are willing and able to draw on
these sources of wealth. By contrast, there is a high share of households with variable rate loans
(on average between May 2015 and May 2016, 52% of new loans had variable rates), which
means that even small changes in interest rate levels can have an impact on household disposable
income. This may lead to larger fluctuations in private consumption and reduce macroeconomic
stability. This, in turn, could lead to negative spillover effects on the banking sector through secondround effects.
Overall, the high and rising RRE prices and existing household indebtedness could interact, leading
to a further increase in overall indebtedness and the proportion of vulnerable households. The
policy actions by the domestic authorities addressing RRE risks have so far focused on increasing
the resilience of the banking sector. Partially, this has been done by increasing risk weights on high
LTV mortgages as well as by applying capital buffers both to the sector and to systemically

124

Based on a recent survey conducted by the Commission de Surveillance du Secteur Financier (CSSF) for the main banks
involved in mortgage lending.

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125

important institutions. On 1 July 2016 a recommendation (CRS/2016/004 ) was issued by the
Luxembourg Systemic Risk Committee to introduce a risk weight floor of 15% on RRE exposures
for IRB banks. These measures will further increase banks’ resilience and risks linked to the
banking stretch seem limited at present. Given that the Luxembourg banking sector is well
capitalised with limited direct exposures to residential real estate, this suggests that the policy
stance for the banking stretch is both appropriate and sufficient. This is also supported by the
evidence from the CSSF stress tests.
Besides taking measures to require that banks have appropriate internal governance and policies
with respect to the mortgage market, no macroprudential measures have been taken to reduce
vulnerabilities linked to the potential negative interaction between household indebtedness and
RRE price dynamics. Borrower-based macroprudential instruments are currently not available to
the Luxembourg authorities. For this reason, a further build-up of vulnerabilities and risks –
especially in the light of the current RRE price and mortgage credit dynamics, the low interest rate
environment and tax deductibility – could not be addressed rapidly with targeted measures. Overall,
given the level and dynamics of identified vulnerabilities, the policy stance regarding the RRE
sector in Luxembourg may not be appropriate to address the vulnerabilities identified for the
collateral stretch. Furthermore, the policy stance for the household stretch is appropriate but not
expected to be sufficient.

Table LU.1
Summary assessment – Luxembourg
Summary RRE risk
assessment narrative

Key risks are related to the collateral and household stretches
The main vulnerabilities are considered to be the combination of high RRE prices and increasing household
indebtedness.
Prices are currently at an unprecedentedly high level, and are increasing both in relation to income and the level of
rents (in Q1 2016 nominal prices increased 4.5% annually, the PTI index increased by 6 p.p. annually and the PTR
index increased by 4 p.p. annually). These price developments have been sustained by structural factors.
Regarding household indebtedness, the latest DTI figure suggests that debt is high (the DTI was 149% in Q1 2016),
while the debt-to-GDP ratio appears to be more muted at 57% in Q1 2016.
On average, the LTV and DSTI ratios in Luxembourg’s mortgage market are robust and represent a mitigating factor.
However, the distribution of the LTV and DSTI ratios both for new and outstanding mortgages suggests that there is
a notable share of loans with high LTV and DSTI ratios that could lead to negative direct and indirect effects on
financial stability in the event of economic or financial shocks. Moreover, household debt for house purchases is
increasing rapidly (an annual growth rate of 6% in June 2016).
The majority of mortgages are variable rate loans (on average between May 2015 and May 2016, 52% of new loans
had variable rates).

Policy assessment given
risks

125

The policy stance is not appropriate and not sufficient for the collateral stretch, and appropriate but not
expected to be sufficient for the household stretch.
Given the level and dynamics of identified vulnerabilities, the policy stance regarding the RRE sector in Luxembourg
is deemed not appropriate, and therefore also not sufficient, due to a lack of policy measures to address collateral
stretch.

Available here:
http://www.bcl.lu/fr/stabilite_surveillance/CRS/Avis_Recommandation_CRS_00_2016_RWfloor_01_07_2016.pdf.

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Table LU.2
Summary of risks and policy measures – Luxembourg
Household stretch

Collateral stretch

Banking stretch

Summary risk assessment/main
risks

Mortgage credit has been
increasing rapidly in recent years
and the level of mortgage debt is
high in relation to the disposable
income of Luxembourg households.
Households’ debt is currently 149%
of their disposable income and it is
still rising (mortgage credit grew by
6% annually in mid-2016), while
mortgage loans are mostly with
variable rates.
A group of mortgage holders may
be vulnerable to unexpected
changes in the real estate market
or the general economy. In 2015,
8% of new loans had an LTV ratio
above 100% and 42% had a DSTI
ratio higher than 40%.

RRE prices in Luxembourg have
been increasing steadily for some
time. Prices are currently at an
unprecedentedly high level, and are
increasing in relation to both
income and the level of rents.
These price developments have
been sustained by structural
factors.
Despite LTV ratios on average
being relatively moderate, their
distribution shows rather high
exposure to possible risks (4% of
the stock of loans had an LTV ratio
higher than 100% in 2015).

Mortgage growth in Luxembourg is
one of the fastest in the EU;
however, banks’ exposure to the
RRE sector is rather small.
Banks in Luxembourg are well
capitalised.

Summary of policy measures
(implemented, planned, under
consideration)

Implemented:
CSSF Circular 12/552 requiring
banks to have appropriate internal
governance and policies, including
with respect to testing mortgagors’
repayment capacity and stricter
stress tests for mortgage books
(2012)

No measures in place or under
consideration

Implemented:
Institutions using the SA for credit
risk need to apply a risk weight of
75% to the part of the mortgage
loan exceeding 80% of the value of
the real estate object
Institutions using the IRB approach
have to ensure that their regulatory
capital adequacy is subject to a
stress test which considers the
effects of severe, but plausible,
recession scenarios
Capital conservation buffer
introduced at 2.5% without phase-in
starting in 2014
Pillar 2 measures are imposed on
four banks operating in the RRE
market
The six main credit institutions in
Luxembourg, of which 3 are
involved in the RRE market, are
subject to O-SII requirements of
0.5-1.0%
Recommendation (CRS/2016/004)
to introduce a risk weight floor of
15% on RRE exposures for IRB
banks

Assessment of policy measures

Appropriate but not expected to
be sufficient

Not appropriate and not
sufficient

Appropriate and sufficient

Household stretch
The main vulnerability in the household stretch is related to the high and increasing debt of
126
households in Luxembourg. The debt-to-income ratio is relatively high at 149% in Q1 2016.
Furthermore, loans for house purchases increased by 6% annually in June 2016, following similarly
rapid credit growth in previous years. By contrast, developments in the debt-to-household assets
ratio appear less pronounced (see Chart LU.1). In addition, vulnerabilities appear to be intensified
by the low interest rate environment. Moreover, the predominance of variable interest rate
mortgages makes households sensitive to a potential rise in interest rates.

126

Based on a recent survey conducted by the CSSF for the main banks involved in mortgage lending. Due to data availability
issues, no reliable LTI data could be provided.

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The average LTV ratio is low for the stock of mortgages at 48% and for new loans at 67%.
However, there is a notable share of loans with high LTV and DSTI ratios. In particular, for 25% of
the loan stock the LTV ratio was higher than 80%, and 4% had an LTV ratio higher than 100% in
2015. As for new loans, the shares are even higher: 40% and 8%, respectively. A similar situation
can be observed for the DSTI ratio, where 27% of the loan stock had a DSTI ratio higher than 40%,
while the share for new loans was 42% in 2015.
There are two different types of risks associated with this. First, while the vulnerabilities in the
household stretch are already elevated given the aggregate level of household debt, there is a risk
that the share of highly indebted households increases further with the ongoing robust growth in
RRE prices and housing loans. Second, in the event of unexpected changes in the real estate
market or the broader real economy (e.g. shocks to economic growth, income or unemployment),
the associated negative household income and wealth effects (e.g. if households need to reduce
consumption in order to service their mortgage loans) may reinforce the initial shock, leading to
deeper economic consequences as well as negative direct and indirect effects on financial stability.
Mortgage debt is not concentrated in certain households, so any income or interest rate shock is
likely to be more widely distributed across the Luxembourg economy.
It should be noted that households in Luxembourg have significant wealth; however, it has been
decreasing with respect to debt over the last couple of years. Also, the average maturity of
mortgage loans is relatively short, at about 21 years, so households in Luxembourg tend to
amortise their liabilities rather quickly. Factors potentially increasing vulnerabilities through
borrowers’ incentives relate to the decisions by the Luxembourg authorities to reduce the taxation
of capital gains derived from the sale of residential property, as well as to increase the mortgage
interest deductibility limit for the principal residence. However, these tax incentives are temporary
and will end in 2017.
No macroprudential measures have been adopted by the Luxembourg authorities to mitigate risks
and vulnerabilities in the household stretch. However, the CSSF has introduced some other
relevant measures: banks are required to test mortgagors’ repayment ability and there are stricter
stress-test requirements on banks’ mortgage portfolios. These measures are appropriate to
address vulnerabilities in the household stretch. However, they are not expected to be sufficient
given that household debt levels are already high and may further increase with the ongoing robust
growth in RRE prices and housing loans. Borrower-based macroprudential tools are currently not
available to the Luxembourg authorities. For this reason, a further build-up of vulnerabilities –
especially in the light of the current RRE price and mortgage credit dynamics, the low interest rate
environment and mortgage interest tax deductibility – could not be addressed rapidly with targeted
measures.

Collateral stretch
Residential real estate prices in Luxembourg have been increasing steadily for some time. Prices
are currently at an unprecedentedly high level (based on available data), and are increasing both in
relation to income and the level of rents. The PTI index increased by 6 p.p. annually to 118% in Q1
2016 and the PTR index increased by 4 p.p. to 119% (both with a value of 100 in 2010). Hence,
prices appear to be high in comparison with fundamentals. In addition, the ECB calculations
suggest that RRE prices are overvalued by 9-18% in Q1 2016. However, calculations by the BCL
show a more conservative degree of overvaluation, with RRE prices more in line with
fundamentals.

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There are several reasons for such a strong increase in RRE prices: (i) growing domestic demand
fuelled by positive demographic changes (positive net migration and an increasing number of
households) and the rising volume of mortgages in the country; (ii) international demand financed
by other sources than domestic banks; (iii) government policies that have further supported housing
demand, for example the increase of the mortgage interest tax deductibility limit for the principal
residence; and (iv) supply-side limitations on the availability of housing.
As for the housing stretch, no macroprudential policy measures are in place for the collateral
stretch. However, some indirect positive effects could stem from increased risk weights on high
LTV mortgages of banks using the standardised approach (SA) and representing some 20% of
market share. As mentioned earlier, the average LTV ratio is low for the stock of mortgages at 48%
and for new loans at 67%. However, taking into account that a relatively high share of mortgages in
Luxembourg have LTV ratios that are above the limits commonly used in other countries (see
127
above) , the exposure to possible vulnerabilities in the real estate market is relatively high and
could lead to both direct and indirect financial stability risks. Given the identified vulnerabilities and
due to the lack of policy measures, the policy stance for the collateral stretch is not appropriate.

Banking stretch
Mortgage loan growth in Luxembourg – at 6.2% in June 2016 – is currently one of the fastest in the
EU, but it has shown a slowing trend over the last four years. However, the share of mortgages in
total loans is relatively small. Moreover, the capitalisation of banks is relatively high in terms of the
CET1 ratio (34.5% in Q1 2016). A capital conservation buffer of 2.5% has been in place since
January 2014, and several mortgage banks have been identified as systemically important with
additional buffers of 0.5%. According to sensitivity analysis performed by the CSSF, in the event of
a severe RRE price shock, combined with a sharp rise in default rates, the main Luxembourg banks
would have enough capital to absorb potential credit losses.
It is also worth mentioning that further measures are expected in order to enhance banks’ resilience
to real estate risks. On 1 July 2016 the Luxembourg Systemic Risk Committee issued an opinion
and a recommendation to the CSSF stating that the average risk weights for IRB banks’ retail (nonSME) exposures secured by residential property should not fall below 15%. Currently, banks using
the SA are required to apply increased risk weights (75%) to high LTV mortgages.
Overall, evidence that Luxembourg’s banks are well capitalised and have low direct exposures to
residential real estate suggests that the policy stance for the banking stretch is both appropriate
and sufficient. This is also supported by the evidence from the CSSF sensitivity analysis. The
robustness of the banking sector to real estate risks will be further strengthened by the measures to
increase the risk weight floors for the IRB banks.

127

See for instance Table 2 in A review of macro-prudential policy in the EU one year after the introduction of the
CRD/CRR, ESRB, June 2015.

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Table LU.3
Additional information on instruments and data available to micro and macro supervisory
authorities – Luxembourg
Do the macro and micro supervisory
authorities have the powers necessary to
implement/amend policy quickly and
effectively if/when required?

Luxembourg’s macro and micro supervisory authorities do not have the power to impose
LTV/LTI/DSTI limits. These powers are not established in Luxembourg law.
Microprudential decisions are taken via the JSTs or, for LSIs, directly by the CSSF (shared
competence).
Macroprudential decisions are taken at the national level by the CSSF in close cooperation
with the BCL, after having received recommendations from the Luxembourg Systemic Risk
Board, and after engaging in the concertation mechanism with the ESCB Financial Stability
Committee and the ESRB, where applicable.

Do the macro and micro supervisory
The Luxembourg authorities have at their disposal a relatively good range of data needed to
authorities have the necessary data to monitor assess the financial stability of the sector. However, there are some data gaps mainly in the
the risks and the impact of policy measures?
LTV distribution and the authorities do not have information on LTI/DTI/DSTI ratios.

Annex with charts
Chart LU.1
Household indebtedness
(percentage)
ratio of total debt to households' assets (right axis)
ratio of total debt to disposable income (left axis)
160

80

140

70

120

60

100

50

80

40

60

30

40

20

20

10

0
Q1 2002

0
Q1 2005

Q1 2008

Q1 2011

Q1 2014

Source: Banque centrale du Luxembourg.

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Malta
Key points
The main vulnerabilities related to residential real estate in Malta concern the household and
collateral stretches. In terms of household stretch, total debt has grown rapidly due to robust
mortgage growth in recent years. The annual growth rate of mortgages started to accelerate from
the beginning of 2014, and reached its peak in the second half of 2015. Over 2015 loans to
households for house purchases increased by 8.5% in Malta. During the first half of 2016 mortgage
growth decelerated somewhat, but has remained rapid at 6.6% on an annual basis on the back of
robust economic growth in Q2 2016 (5.2% year-on-year). Aggregate debt is relatively high in
relation to households’ income. Total financial liabilities of households constituted approximately
70% of GDP in 2015, which is close to the euro area average. However, total financial liabilities in
comparison to wages were significantly higher in Malta than in the euro area, and reached nearly
160% (the euro area average is around 140%). The latest macroeconomic forecast by the
European Commission projects slowing, though still robust, growth of Malta’s economy for this and
next year. Thus, households’ indebtedness relative to income and to GDP is expected to increase
128
further in the medium term. The debt service-to-income ratio , at 13%, is relatively high in Malta
compared with other EU countries, despite the prevailing low level of interest rates.
Mitigating factors include that only around 16% of Maltese households have a mortgage (relative to
the EU average of 27%) and the large holdings of financial assets by Maltese households should
129
be a buffer if risks related to residential real estate manifest themselves. In addition, while the
majority of mortgages are with variable rates, it is a common practice in Malta that when interest
rates change, banks maintain the same annual repayment requirements but adjust the term to
maturity. This means that debt servicing costs would not be expected to rise even when interest
rates rise.
In terms of collateral stretch, the official transaction-based RRE price data showed 2.6% annual
growth, whereas advertised prices increased by 9.9% in Q1 2016. Both price indices have passed
their highest levels reached before the last financial crisis, by 1.4% and 16.7% respectively.
Different RRE price valuation methods indicate that, on average, real estate prices in Malta are
broadly in line with fundamentals. However, the experience of some countries shows that
advertised RRE prices, which are at their all-time high level and rising rapidly in Malta, could act as
a leading indicator for transaction prices. Thus, monitoring of RRE prices should continue to be a
high priority for the Maltese authorities.
There are several structural and other factors that might mitigate potential RRE price declines.
These include the limited amount of land available for construction and the low supply of housing.
They also include a growing population, net migration and a generally high home-ownership rate
(where many households do not have mortgages). However, there are also some factors that might
cause misaligned incentives and/or lead to excessive housing demand. For instance, temporary tax

128

For more details, see Drehmann, M., Illes, A., Juselius, M. and Santos, M., “How much income is used for debt
payments? A new data base for debt service ratios”, BIS Quarterly Review, September 2015. Note that due to
comparability issues, as for the denominator, compensation of employees has been used; thus, differences may appear by
using other data sources (e.g. disposable income). For example, using the Central Bank of Malta (CBM) estimates for
disposable income, the DSTI ratio for the corresponding period goes down to 9.3%.

129

Information about holdings of financial assets is from the H2, 2013 CBM Household Finance and Consumption Survey (the
latest available).

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advantages for first-time buyers (stamp duty relief is due to expire by the end of 2016) and the
Individual Investor Programme, which seeks to incentivise people to move to and reside in Malta,
may lead to excessive growth in prices and mortgages. However, the latter programme has not so
far resulted in significant purchases of property.
Regarding the banking sector stretch, the banking sector in Malta is very large and concentrated,
and has strong links with the real estate sector. In terms of assets, the total banking sector exceeds
by five times the size of the total economy. However, when taking into account the assets of those
banks that are linked with the domestic economy, the ratio of assets to GDP declines to 2.6 (core
and non-core domestic banks). Mortgage loans to households, loans for construction and loans to
real estate-related companies constituted 11% of total bank assets at the end of 2015 – the highest
level since the start of data in 2005 – and amount to 59% of GDP. Banks and the real economy in
general (in terms of value added and investment) are becoming more interlinked and are thus more
exposed to risks in the real estate sector. In addition, given strong economic growth and the low
level of unemployment, the NPL ratio for mortgages could be considered relatively high (3.1% in Q1
2016). However, Maltese banks are highly capitalised (CET1 ratio of 21.0% in Q1 2016), have
favourable liquidity positions (market funding is low and deposits are the predominant form of
funding (approx. 80%) for Maltese core domestic banks) and have comparatively high risks weights
applied to real estate exposures (35-100%, with an average of approx. 39%), reflecting
implemented policy measures.
The Maltese authorities have implemented both micro- and macroprudential measures to mitigate
vulnerabilities regarding the banking stretch. Since 2008 they have required banks to apply higher
RRE risk weights to the portion of a mortgage loan with an LTV greater than 70%. Thus, it is more
130
expensive for banks in terms of the capital charge to issue highly leveraged mortgage loans. The
authorities also apply microprudential measures to ensure that banks hold sufficient reserves for
the stock of non-performing exposures (a specific reserve equivalent to 2.5-5%, depending on the
overdue period). The fact that the bulk of non-performing exposures in Malta are related to the
construction sector indirectly acts as an incentive for banks to act prudently in this sector, hence
bolstering the resilience of credit institutions further. Furthermore, the O-SII buffer and the capital
conservation buffer are currently being phased in and the countercyclical capital buffer has been
activated (currently set at 0%).
So far, no borrower-based macroprudential measures have been applied in Malta to directly
address vulnerabilities related to household and collateral stretches. However, it is positive that
there are no legal impediments that would hinder the deployment of such instruments (such as LTV
or LTI limits) and thus they could be deployed rapidly if necessary. The Maltese authorities have
identified that there is a lack of granular data on the distribution of household indebtedness and its
evolution, and are currently undertaking a data collection exercise to improve this. These data will
be important in order to make a fully comprehensive risk assessment.
Overall, the policy stance is considered to be appropriate and expected to be sufficient in Malta at
the current juncture given the current level of risks from the RRE sector. While some vulnerabilities
relating to the household and collateral stretches have been identified in Malta, these are mitigated
by several factors and are assessed not to present systemic risks at present. The micro- and

130

Mortgages secured by residential property are assigned a risk weight of 35% for loans not exceeding 70% of the market
value of the property (rather than 80% of the market value of the property as in the CRR). For any remaining part of the
loan, a risk weight of 100% is assigned, in accordance with Article 124(1) of the CRR.

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macroprudential measures targeted at banking stretch are also assessed to be appropriate and
expected to be sufficient, particularly given the high capitalisation of the banking system and high
risks weights applied to RRE exposures. However, it is important that the Maltese authorities
continue to monitor the evolution of RRE prices (particularly the potential link between advertised
and transaction-based prices) and lending standards due to rapid mortgage growth, and that they
ensure access to and analyse more granular data with respect to household stretch.

Table MT.1
Summary assessment – Malta
Summary RRE risk
assessment narrative

The main RRE-related vulnerabilities in Malta concern the collateral and household stretches
The rapid growth of households’ total debt due to robust mortgage growth, and the relatively high debt level and
debt service burden in relation to households’ income.
During the first half of 2016 mortgage growth decelerated somewhat, but remained rapid at 6.6%. Total financial
liabilities of households constituted approximately 70% of GDP in 2015, which is the euro area average. However,
total financial liabilities in comparison to wages (compensation of employees) were significantly higher in Malta
than in the euro area, and reached nearly 160% (the euro area average is around 140%). The debt service-toincome ratio is relatively high in Malta (at 13%) despite the currently prevailing low level of interest rates. However,
using the Central Bank of Malta estimates for disposable income, the DSTI ratio for the corresponding period goes
down to 9.3%.
In terms of collateral stretch, the official transaction-based RRE price data showed 2.6% annual growth, whereas
advertised prices rose by 9.9% in Q1 2016. Both price indices have passed their peaks reached before the last
financial crisis, by 1.4% and 16.7% respectively. Different RRE price valuation methods indicate that, on average,
real estate prices in Malta are broadly in line with fundamentals.

Policy assessment given
risks

The policy stance is appropriate and expected to be sufficient
Overall, the policy stance is considered to be appropriate and expected to be sufficient in Malta at present given
the current level of risks from the RRE sector.
While some vulnerabilities relating to the household and collateral stretches have been identified in Malta, these
are mitigated by several factors and are assessed not to present systemic risks at present. There are no
impediments in national law hindering a rapid deployment of borrower-based measures should vulnerabilities
increase.
A number of micro- and macroprudential measures have been taken to address direct risks to the banking sector
stemming from RRE vulnerabilities. These are assessed as appropriate and expected to be sufficient, particularly
given the high capitalisation of the banking system and high risks weights applied to RRE exposures.
It is important that the Maltese authorities continue to monitor the evolution of RRE prices and lending standards
due to rapid mortgage growth, and that they ensure access to and analyse more granular data with respect to
household stretch.

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Table MT.2
Summary of risks and policy measures – Malta
Household stretch

Collateral stretch

Banking stretch

Summary risk assessment/main
risks

Rapidly increasing aggregate level
of household indebtedness, which
has, however, been slower than the
increase in households’ assets.
Total financial liabilities in
comparison to wages
(compensation of employees) are
significantly higher in Malta than in
the euro area, and reached nearly
160% in 2015 (the euro area
average is around 140%).
Mortgage growth is among the
most rapid in Europe, on the back
of robust economic growth.
Debt service ratio is relatively high
historically.

The official transaction-based RRE
price data showed 2.6% annual
growth, whereas advertised prices
rose by 9.9% in Q1 2016. Both
price indices have passed their
peaks reached before the last
financial crisis, by 1.4% and 16.7%
respectively.
Different RRE price valuation
methods indicate that, on average,
real estate prices in Malta are
broadly in line with fundamentals.
However, average LTV ratios are
moderate so there is a buffer
against RRE price falls.

The banking sector in Malta is very
large 131 compared with the size of
the economy and is very
concentrated, but also highly
capitalised.
Mortgage loans to households,
loans for construction and loans to
real estate-related companies
constituted 11% of total bank
assets at the end of 2015 – the
highest level since the start of data
in 2005 – and amount to 59% of
GDP. Banks and the real economy
in general (in terms of value added
and investment) are becoming
more interlinked and thus more
exposed to risks in the real estate
sector. However, banks apply
comparatively high risks weights to
real estate exposures (35-100%).
The share of non-performing loans
in the household sector is relatively
high (but declining) despite recent
robust economic growth (5.2%
year-on-year growth in Q2 2016).

Summary of policy measures
(implemented, planned, under
consideration)

No measures in place or under
consideration

No measures in place or under
consideration

Risk weights depend on the LTV:
35% RW if the LTV <70% and
100% RW for the remaining part of
the loan with the LTV >70%
(slightly more stringent than the
CRR standardised approach rules)
Pillar 2: reserves for general risks
due to heightened level of NPLs
CCoB: 0.625% (rising to 2.5% by
2019)
O-SII buffer: 0.125-0.5% (rising to
0.5-2.0% by 2019)
CCyB: 0%

Assessment of policy measures

Appropriate and expected to be
sufficient given that identified
vulnerabilities are mitigated by
several factors and, therefore, are
assessed not to be material
currently

Appropriate and expected to be
sufficient given that there are no
clear signs of overvaluation,
excessive RRE price dynamics
(based on the official price index) or
weakening lending standards at
present

Appropriate and expected to be
sufficient

Household stretch
In Malta, vulnerabilities in the household stretch relate to the rapid growth of households’ total debt
due to rapid mortgage growth, and the generally relatively high debt level and debt service burden
relative to households’ income. However, only around 16% of households had mortgages, which is
significantly less than the EU average (27%). In addition, aggregate information and the somewhat
outdated household survey data confirm that the large holdings of financial assets by Maltese
households can act as an effective buffer against the materialisation of RRE risks.
In 2015 total financial liabilities (of which more than 80% are loans) grew by 5.3%, which is
relatively high in comparison to other EU countries. This was mainly driven by the growth of loans
for house purchases provided by banks. In fact, loans to households for house purchases

131

For core and non-core domestic banks (with links only to the domestic economy), the ratio of assets to GDP is 2.6.

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increased by 8.5% over 2015, on the back of robust economic growth. The annual growth rate of
mortgages started to accelerate from the beginning of 2014, and reached its peak in the second
half of 2015. During the first half of 2016 mortgage growth decelerated somewhat, but remained
rapid at a 6.6% annual growth rate.
Total financial liabilities of households constituted approximately 70% of GDP in 2015, which is the
euro area average. However, total financial liabilities in comparison to wages (compensation of
employees) were significantly higher in Malta than in the euro area, and reached nearly 160% (the
euro area average is around 140%). The latest macroeconomic forecast by the European
Commission projects slowing growth of Malta’s economy for this and next year (though still
remaining robust); thus, households’ indebtedness relative to income and to GDP is expected to
increase further.
The debt service-to-income ratio is relatively high in Malta, at 13%, despite the currently prevailing
132
low level of interest rates and the fact that the majority of mortgages are variable rate mortgages.
However, according to the Maltese authorities, banks in Malta are keeping monthly mortgage
payments constant by shortening loan maturities to compensate for the decrease in interest rate
payments due to the low interest rate environment. The increase in the amortisation rate should
positively contribute to the mitigation of vulnerabilities. Based on survey information, the weighted
average maturity for new residential loans is around 26 years, while the weighted average maturity
for first-time buyers is almost 31 years. The maturities are quite close to the EU averages.
At the aggregate level, the relatively large holdings of financial assets mitigate vulnerabilities
related to households’ indebtedness in Malta. Overall, households have nearly four times more
financial assets than liabilities and, since 2009, financial assets have grown more rapidly than
liabilities. Usually, the majority of households’ financial assets are made up of equity, but in Malta
almost half of such assets are in currencies and deposits, i.e. they are highly liquid. In fact,
households’ holdings in bank accounts exceeded the loan stock for house purchase at the end of
2015 by almost 50%. Furthermore,the share of household debt in financial assets has been
decreasing and is below the EU figures. This suggests that, on aggregate, households are well
prepared for possible shocks.
However, one needs to analyse micro-level data to better understand potential vulnerabilities facing
133
households with mortgages. According to a 2013 household survey , almost 80% of Maltese
households were owner-occupiers of their homes, with the median value of their main residence
estimated at around €187,000. Furthermore, the median value of households’ financial asset
holdings was estimated at around €26,000. One-third of all households had some type of debt
liability averaging around €36,000. According to the survey, household debt represents only 3% of
the total gross wealth of households. However, from these and other results it is not clear whether
mortgage holders have a financial buffer to cover at least part of their debt if economic performance
were to deteriorate.

132

This ratio of 13% is a macro-level aggregated figure based on BIS statistics. Using the Central Bank of Malta estimates for
disposable income, the DSTI ratio goes down to 9.3%. Recent preliminary survey results for Malta show that the DSTI ratio
at loan origination for those households that actually have debt stood at 24.6%.

133

“Household Finance and Consumption Survey in Malta”, Quarterly Review, 2013:2, Central Bank of Malta.

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134

As the results of the ECB household survey suggest, only around 16% of households had
mortgages, which is significantly less than the euro area average of around 23%. Eurostat’s SILC
survey provides slightly different shares (20% and 28% respectively; 27% for the EU), but the
tendency is the same. The median ratio of household debt to gross household income was 52%.
When this ratio is calculated solely for those households with mortgage debt as their debt liability,
the ratio increases to 151%. However, two-thirds of their debt is covered by financial assets. In fact,
Maltese households with mortgages would be able to cover their monthly payments from their
holdings of financial assets for more than six years. Given that this information is already some
years old, it would be important to be able to make the assessment of vulnerabilities related to
household stretch using more up-to-date information. The Maltese authorities are currently
collecting this information and it should be available around October/November 2016.
No borrower-based macroprudential measures have been implemented to address household
stretch in Malta yet. However, only about 16% of Maltese households have mortgages and the
aggregate information and the somewhat dated household survey data confirm the relatively large
holdings of financial assets by Maltese households, which can act as an effective buffer against the
materialisation of RRE risks. Given these mitigating factors, the RRE-related risks in the household
135
stretch are assessed to be low at the moment and, therefore, the policy stance of no borrowerbased macroprudential measures is assessed as expected to be sufficient. However, given that the
available household-level information is already some years old, it would be important to be able to
make the assessment of vulnerabilities related to household stretch using more up-to-date
information, particularly given the rapid mortgage credit growth and dynamics in RRE prices
(particularly in the advertisement-based price index).

Collateral stretch
Residential real estate prices in Malta are increasing. Depending on the price series used, in Q1
2016 they picked up by between 2.6% and 9.9% in terms of annual growth rates, based on the
Eurostat RRE price index and the Central Bank of Malta’s asking price-based index, respectively.
The trend in RRE price growth has accelerated since mid-2013, and the current price levels are at
all-time high levels. The transaction-based RRE price index has passed the peak reached before
the financial crisis by 1.4%, and the advertisement-based price index has exceeded its peak before
136
the financial crisis by 16.7%. The official assessment of RRE prices is based on transaction
prices. However, experience of some countries shows that advertised prices could act as a leading
indicator for transaction prices. Thus, the monitoring of RRE prices should be a high priority for the
Maltese authorities.

134

“The Eurosystem Household Finance and Consumption Survey: results from the first wave”, Statistical Paper Series,
No 2, ECB, April 2013. According to our knowledge, the survey data was collected in 2010-11.

135

It should be noted that given a high home-ownership rate, a shock to residential real estate prices could lead to significant
wealth effects and negative consumption developments.

136

The housing price (HP) index that has been used by the Central Bank of Malta, as well as many international organisations
(BIS, IMF) in their analysis of Malta, has been the HP index based on the advertised residential property price index. This
differs from the property price index collected and published by Malta’s National Statistical Office which is based on actual
transactions covering many different housing forms (Eurostat definitions). According to the actual transaction-based HP
index, RRE price growth has been more moderate compared with the advertised price-based HP index. In the Central Bank
of Malta’s Annual Report, the year-on-year growth in the advertised price index was 5% on average, and 3.9% for the
actual transaction-based HP index (for the first three quarters of 2015). In its analysis, the ECB’s DG/MF used both HP
indices and found the same results for the riskiness of Malta’s RRE market (medium risk).

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Different RRE price valuation methods indicate that, on average, real estate prices in Malta are
broadly in line with fundamentals. Changes of real estate prices in relation to household income
have stayed stable since 2012 (in the previous years, RRE price growth was more rapid than
income growth, suggesting some overvaluation). The dispersion among different valuation methods
has widened recently and indicates both under- and overvaluation signals, which illustrates the
uncertainty regarding valuations in the RRE sector. Were economic and income growth to slow
down in Malta, this would be expected to be reflected in RRE price valuations. The latest
macroeconomic forecast by the European Commission projects slowing, though still robust, growth
of Malta’s economy for this and next year.
Changes in RRE price valuations may have an impact on the economy. Value added by
construction and real estate activities in Malta is lower than before the crisis. However, in 2015, its
share increased somewhat to nearly 9% of GDP, which is relatively high at the European level.
Investments in dwellings have increased in the past two years and the number of building permits
granted resumed its rise. In 2014 the number of housing transactions was at the highest level in the
last eight years. Thus, the importance and activity of the real estate market in Malta is increasing,
which warrants its close monitoring.
As mentioned for the household stretch, mortgage credit growth in Malta is among the strongest in
Europe. In Q2 2016 it decelerated slightly, but remained at the rather elevated level of 6.6% per
year. The changes in RRE prices and in mortgages have recently become more interlinked: the
statistical correlation between movements in the housing price index and the mortgage credit stock
is strong in Malta; growth in the mortgage credit stock by one indexed point is associated with RRE
price growth by 0.2 indexed point. In such a context, the high growth rate of mortgages may push
real estate prices up in an unsustainable way.
There are several demand-side factors affecting the Maltese RRE market and RRE price growth.
The population is growing quickly, immigration has exceeded emigration, the employment
participation rate is increasing, and the unemployment rate is declining. In May 2016 the
unemployment rate in Malta was 4.1%, which is one of the lowest in Europe and is expected to
decrease further. Given relatively stable earnings in the last couple of years, the purchasing power
of households has increased. Taking into account the low interest rate environment, it is not
surprising to observe growth of investment in comparatively profitable real estate. Other relevant
factors are the temporary fiscal incentives for first-time buyers and the Individual Investor
137
Programme (IIP) designed to attract applicants to Malta’s shores. However, the amount of the
programme is small: out of 143 applicants, only 27 persons have actually purchased a property in
Malta, with the remaining 116 renting properties.
There are also some important supply-side factors, such as the limited amount of available
construction land and the limited supply of housing, which can have an impact on the RRE market
and prices. House construction volume growth has been slower than that in general economic
activity. Moreover, dealing with construction permits in Malta is slightly more difficult than on
average in other OECD countries based on World Bank Doing Business data. However, as the
Maltese authorities point out, height restrictions in highly urbanised areas have been relaxed

137

The IIP is the first citizenship programme in the European Union to be recognised by the European Commission. Applicants
are subject to a thorough due diligence process, which guarantees that only reputable applicants acquire Maltese
citizenship.

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recently, which is expected to alleviate some supply constraints. Over the last five years,
construction prices have increased by almost 10%.
For individual borrowers, the LTV ratio for mortgage loans is higher than the EU average of approx.
70%; the average LTV ratio for new loans to first-time homebuyers is around 77% and around 74%
for non-first-time buyers. While LTV ratios are currently not far above average in Malta, there is a
risk that lending standards could deteriorate in the future if the trend of rapid credit growth
continues.
So far, no macroprudential measures have been taken to tackle the vulnerabilities in the collateral
stretch. The official transaction-based RRE price data showed 2.6% annual growth in Q1 2016,
while the price index has passed the peak reached before the financial crisis by 1.4%. Regarding
the RRE price valuations, the dispersion among different valuation methods has widened recently,
pointing to both under- and overvaluation, which illustrates the uncertainty regarding valuations in
the RRE sector. However, mortgage credit growth in Malta is among the strongest in Europe (in Q2
2016 it was 6.6% per year).
Given the moderate RRE price developments in the official transaction-based RRE price index and
no clear signs of overvaluation of RRE prices, the policy stance of no macroprudential policies is
assessed as expected to be sufficient. However, experience of some countries shows that
advertised prices, which increased by 9.9% in Q1 2016 and are at their all-time high level, could act
as a leading indicator for transaction prices. Thus, the monitoring of RRE prices should be a high
priority for the Maltese authorities.

Banking stretch
138

The banking sector in Malta is assessed to be resilient to RRE vulnerabilities , given the high risk
weights applied to RRE exposures and the overall high solvency and liquidity ratios. However, its
biggest vulnerabilities relate to the large size of the banking sector relative to the economy and
banks’ increasing exposures to the real estate and construction sectors.
Overall, the Maltese banking sector is well capitalised, and all solvency and liquidity ratios are well
above the minimum requirements. Banks’ CET1 capital ratio in Q1 2016 stood at 21%, which was
relatively high in the European context but rather low from a Maltese historical perspective.
Moreover, the risk weights on RRE exposures are very high in an international context as all banks
use the standardised approach. Average risk weights on RRE exposures are around 39% for the
moment. The funding structure of banks in Malta suggests that the banking sector’s dependency on
market funding is low: the loan-to-deposit ratio is 50% in consolidated terms. Deposits are the
predominant form of funding (approx. 80%) for Maltese banks.
The banking sector in Malta is very large and concentrated and has become more interlinked with
the real estate sector. In terms of assets, the banking sector exceeds the total economy by five
139
times. Mortgage loans to Maltese households, loans for construction and loans to real estaterelated companies as a share of banks’ total assets at the end of 2015 stood at 11.0%, which is the
peak level over an 11-year period. However, in relation to GDP, real estate-related loans stood at
58.9% at the end of 2015 and were on a decelerating trend. However, the exposures of core

138

According to the IMF (2016), Maltese banks are well capitalised, profitable and liquid.

139

For core and non-core domestic banks (with links only to the domestic economy), the ratio of assets to GDP is 2.6.

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domestic banks to mortgage loans are 19% of total assets and their exposures to the real estate
sector are 25% of total assets.
The amount of non-performing loans (NPLs) has picked up compared with the situation at the end
of 2013, although in the course of 2015 and 2016 NPLs decreased slightly. The share of banks’
non-performing debt instruments in the total corresponding stock was 5.4% at the end of 2015.
140
According to the Maltese authorities , this is mainly due to the legacy of the past crisis and is
limited to sectors like construction. Banks in Malta have made larger loan loss provisions than in
previous years, approaching 50% of NPLs. The low level of interest rates and high employment are
supporting the repayment of loans. However, the share of non-performing mortgage loans was
3.1% of the mortgage stock in Q1 2016, down from 3.4% in December 2015.
The results of stress tests performed by the Central Bank of Malta indicate that the Maltese banking
sector can withstand extreme yet plausible shocks under a number of scenarios. The lossabsorbing buffers in the banking system are sufficiently large to withstand a drop in collateral
values of at least 30%. Combined with an increase in the level of non-performing loans of up to
10%, banks would remain sufficiently capitalised, with their CET1 ratios remaining above the
regulatory minima given their high levels of loan loss provisions. Moreover, the published results of
the ECB 2014 comprehensive assessment reveal that the participating Maltese banks could
withstand even the more severe scenario with their CET1 ratios ending at levels significantly above
the 5.5% stipulated threshold.
Regarding macroprudential measures, the O-SII buffer is in place (0.125-0.5% and after the
transition period 0.5-2.0% in 2019). Pillar 2 measures for general banking risk are in use by all
banks to mitigate risks arising from the heightened level of NPLs. The capital conservation buffer is
0.625% at present (2.5% in 2019) and the countercyclical capital buffer is 0% at present. In 2008
the Maltese authorities introduced an LTV measure, as a combination of preferential risk weights
and more stringent LTVs. The measure requires that mortgages on residential property attract a
risk weight of 35% on the part of the loan that does not exceed 70% of the market value of the
property and the rest of the loan is assigned a risk weight of 100%.
Overall, Maltese banks are highly capitalised (CET1 ratio of 21% in Q1 2016) and have high risk
weights on real estate exposures (35-100%). Moreover, the Maltese authorities have activated the
O-SII and the capital conservation buffers and have taken Pillar 2 measures. At the same time, the
banks’ direct exposures to mortgages are low at 7.6%. However, banks’ overall exposure to real
estate-related activities (construction, related companies) has risen significantly and the banking
sector is becoming more interlinked with the real economy. Moreover, the share of non-performing
mortgage loans was 3.1% of the mortgage stock in Q1 2016, which is relatively high given the
robust economic developments. Thus, taken together, given the level of RRE-related risks, the
micro- and macroprudential measures taken regarding banking stretch are expected to be
sufficient.

140

IMF (2016), as above fn. 138.

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Table MT.3
Additional information on instruments and data available to micro and macro supervisory
authorities – Malta
Do the macro and micro supervisory
authorities have the powers necessary to
implement/amend policy quickly and
effectively if/when required?

There are no legal impediments in national law to prevent a rapid deployment of borrowerbased macroprudential measures should the authorities want to deploy them.

Do the macro and micro supervisory
The authorities are currently undertaking a granular data collection exercise in order to get
authorities have the necessary data to monitor better micro-level data on the distribution of household debt and to inform future
the risks and the impact of policy measures?
policymaking.

Annex with charts

141

Chart MT.1
Household financial liabilities-to-GDP ratio

Chart MT.2
Share of variable rate loans in total new
loans to the private sector

(percentage)

(percentage)

80

100
70

80

60
50

60
40

40

30
20

20
10
0
Q1 2004 Q1 2006 Q1 2008 Q1 2010 Q1 2012 Q1 2014

Sources: Eurostat and ESRB calculations.

141

0
01/08

01/10

01/12

01/14

01/16

Source: ECB.

All data in these charts are from publicly available sources.

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Chart MT.4
Households’ total financial assets-to-total
liabilities ratio

Chart MT.3
Price-to-income ratio

(index: 2000 = 100; HPI/compensation of employees)

(ratio)

160

5.0

140
4.5

120
100

4.0

80
60

3.5

40
20
0
Q1 2000

Q1 2004

Q1 2008

Q1 2012

Q1 2016

Sources: Eurostat.

3.0
Q1 2004 Q1 2006 Q1 2008 Q1 2010 Q1 2012 Q1 2014

Sources:Eurostat and ESRB calculations.

Chart MT.5
House price indices

Chart MT.6
Valuation of residential real estate prices

(index: 2010 = 100)

(percentage)
minimum valuation measures for all types of property
average valuation measures for all types of property
maximum valuation measures for all types of property

transaction-based HPI
advertise-based HPI
130

40
35

120
110

30
25
20

100

15
10

90
80

5
0
-5

70
60
Q1 2005 Q1 2007 Q1 2009 Q1 2011 Q1 2013 Q1 2015

Sources: Eurostat and BIS.

-10
-15
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Source: ECB.

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Chart MT.8
Value added of real estate-related activities
in comparison to GDP

Chart MT.7
House price indices and credit for
house purchase
(x-axis: Credit, index: 2010 = 100; y-axis: HPI, index: 2010 = 100)

(percentage)
real estate activities
construction
14

115

12

HPI = 0.2*Credit + 74.4
R² = 0.71
110

10
8

Q1, 2016
105

6
4
100
2
Q1, 2011

0
Q1 2000

95
100

110

120

130

140

150

160

Q3 2003

Q1 2007

Q3 2010

Q1 2014

Source: Eurostat.

Sources: Eurostat, ECB and ESRB calculations.

Chart MT.9
Banks’ Tier 1 ratio

Chart MT.10
Mortgage loans-to-total bank assets ratio

(percentage)

(percentage)

9

60

8

50

7
6

40

5

30

4
3

20

2

10

0
2010

1

2011

2012

2013

2014

2015

Source: ECB.

0
2005

2007

2009

2011

2013

2015

Sources: ECB and ESRB calculations.

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Chart MT.12
Share of mortgages and loans to
construction and real estate companies in
banks’ total loan portfolio

Chart MT.11
Banks’ gross non-performing
debt instruments

(percentage share of total gross debt instruments)

(%)

8

60

7

50

6
40
5
30

4
3

20

2
10
1
0
12/07

12/09

12/11

12/13

12/15

Source: ECB.

0
2005

2007

2009

2011

2013

2015

Sources: ECB and ESRB calculations.

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The Netherlands
Key points
The main vulnerability related to residential real estate in the Netherlands is the persistently high
household debt levels combined with low mortgage collateralisation. In particular, there is a large
group of households, especially younger mortgagors, which have debt levels that exceed the value
of their home. While the aggregate household debt-to-income ratio has fallen somewhat over the
past years, it is still high at 231% in Q1 2016 compared with most other EU and developed
countries. The same goes for the household debt-to-GDP ratio, which is high at 111% in Q1
142
2016.
Regarding credit developments, total mortgage lending to households grew annually by 1.1% in Q1
143
2016 (including banks and all other institutions granting mortgage loans). However, loans for
house purchases provided by monetary financial institutions (MFIs) increased annually by 4.0% in
June 2016.
Risks related to the collateral stretch are also elevated. The loan-to-value ratios, at 94% for new
loans and 68% for the stock of loans, are among the highest in the EU. Approximately 25% of all
mortgage holders and 50% of mortgagors under 40 years old have total debt relative to the value of
the home above 100%. Due to low amortisation rates for pre-2013 mortgage debt and since new
mortgage loans tend to be high in relation to the value of the purchased property, the vulnerabilities
related to the high debt level and high LTV ratios are likely to persist. For new mortgage loans,
however, the amortisation rates are higher, because only interest on amortising mortgages may be
deducted for tax purposes, which acts as an incentive for households to amortise their loans.
RRE prices had grown by 4.4% annually in Q2 2016, and they are approaching their pre-crisis
peaks in the major cities, but not in the country as a whole. A mitigating factor is that RRE prices,
144
according to ECB estimates, do not appear to be overvalued. Another mitigating factor is the
strong recourse facilities for lenders, and strict personal bankruptcy rules may limit the direct credit
risk for banks. However, high household indebtedness may lead to considerable indirect negative
effects on macroeconomic and financial stability in the event of an adverse scenario such as higher
unemployment, a rise in interest rates or a fall in RRE prices.
In order to address these risks, the Dutch authorities are gradually tightening the limits on the DSTI
and LTV ratios for new lending and reducing the tax deductibility of mortgage interest. The DSTI
limit has declined over the past years, due to slow growth in households’ disposable income. In
addition, new interest-only mortgages are not tax deductible, which incentivises households to
amortise their loans. Stress tests of banks also indicate that they have sufficient capital in the
adverse scenarios related to real estate developments.
While the policy measures taken for the Netherlands are appropriate given the nature of RRE
vulnerabilities, they may not be sufficient to fully address them as most measures are only being
gradually phased in and their calibration will not be very constraining even after full implementation.

142

The ratio of mortgage debt to GDP is 94.2%.

143

Total mortgage lending started to grow in 2015, after a slight abatement in 2013-14. When corrected for securitisation
operations, the growth rate of mortgage credit provided by MFIs was negative also in the first quarter of 2016.

144

Overvaluation was assessed in the horizontal analysis, i.e. methods used by the ECB and the ESRB. Additionally, results
of real estate price valuations could be found in the ECB Statistical Data Warehouse (RRE prices and RRE price valuation
indicators).

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The vulnerabilities that might not be fully addressed are related to the household and collateral
stretches, while vulnerabilities related to the banking sector seem limited and the measures taken
are assessed as appropriate and sufficient.

Table NL.1
Summary assessment – The Netherlands
Summary RRE risk
assessment narrative

Key risks are related to the collateral and household stretches
The main vulnerabilities are considered to be the persistently high household debt levels combined with low
mortgage collateralisation. In particular, there is a large group of households, especially younger mortgagors, which
have debt levels that exceed the value of their home.
Household debt levels are very high both in comparison with income (the DTI ratio is 231%), GDP (111%) and
house values (the LTV ratio is 94% for new loans and 68% for the stock), despite risk indicators having improved in
recent years.
Total mortgage lending to households by banks and all other institutions granting mortgage loans has been muted
at 1.1%, whereas growth in lending to households by MFIs has been higher at 4% over the last year.
A quarter of homeowners and around 50% of first-time buyers have total debt in excess of the value of their
property.
RRE prices in the cities are approaching peak levels and overall RRE prices in mid-2016 increased by 4.4%
annually.

Policy assessment given
risks

The policy stance is not expected to be sufficient for the collateral and household stretches
Measures are only being gradually tightened at a slow pace over a long time horizon.
Even after full implementation, the LTV limit (100% in 2018) and tax deductibility will still be high.
While the policy measures taken for the Netherlands are appropriate given the nature of RRE vulnerabilities, they
may not be sufficient to fully address them as most measures are only being gradually phased in and their
calibration will not be very constraining even after full implementation.

Table NL.2
Summary of risks and policy measures – The Netherlands
HOUSEHOLD STRETCH

COLLATERAL STRETCH

BANKING STRETCH

Summary risk assessment/main
risks

The main vulnerability is related to
high household indebtedness, as
the debt-to-income ratio is one of
the highest in the EU. The high
debt level is partly due to the tax
system. The relatively low
amortisation rates make the high
indebtedness persistent. Adverse
shocks to households could lead to
lower consumption, which could
harm macroeconomic and financial
stability.

Elevated vulnerability related to the
collateral stretch, as mortgage
portfolios are large and loan-tovalue ratios are high (in particular
for certain households). Underwater
households are expected to be a
persistent problem. RRE prices in
the cities are close to peak levels
after relatively fast increases.

The vulnerability due to banking
stretch is lower than for the other
two stretches. However, leverage of
Dutch banks is high and the banks
rely on market funding. A drying-up
of market funding could trigger risk
materialisation. In addition, almost
half of new loans are currently
provided by non-banks, which could
increase risks to financial stability.

Summary of policy measures
(implemented, planned, under
consideration)

DSTI/LTI limits since 2012, being
gradually tightened (limits depend
on income and interest rates).

Gradual lowering of the LTV limit
for new mortgages from 106% in
2012 to 100% in 2018 (currently
102%).

The systemic risk buffer at 3% and
the O-SII buffer between 1 and 2%
will be phased in between 2016 and
2019. For each bank, the higher of
the two will apply.

Tax deductibility eligibility: new
mortgages must take an annuity or The Dutch Financial Stability
linear form in order for interest to be Committee has recommended to
tax deductible from 2013.
continue the gradual reduction
beyond 2018 to an LTV limit of
90%.
From 2014 the maximum tax
deduction rate will be gradually
reduced over 28 years.
Assessment of policy measures

Appropriate but not expected to
be sufficient

Appropriate but not expected to
be sufficient

The countercyclical capital buffer
has been 0% since 2016.
Macroprudential tools for loans
(LTV limits, etc.) apply to banks and
non-banks.
Appropriate and sufficient

Household stretch
The main RRE vulnerability in the Netherlands is related to high household indebtedness. While the
aggregate household debt-to-income ratio has fallen somewhat over the past years, it is still high at
231% compared with most other EU and developed countries. The same goes for the household

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145

debt-to-GDP ratio, which is high at 111%. In recent years, the growth in total mortgage lending
(including banks and all other institutions granting housing loans in the Netherlands) to households
has been relatively muted at 1.1% in Q1 2016. When corrected for securitisation operations, the
growth rate was even negative in Q1 2016. However, loans for house purchases provided by other
MFIs were growing by 4.0% annually in June 2016.
The average maturity of mortgages is long (about 30 years) and interest-only loans are still
common, which implies that the vulnerabilities are not likely to decrease quickly. However, there
are factors (e.g. a generous tax subsidy for homeowners and strong recourse facilities for lenders)
that reduce the risk of households defaulting on their debt. The main risk is that high household
indebtedness may lead to negative effects for the real economy, with potential negative spillover
effects on the financial sector.
The authorities have introduced measures for both new mortgages and the stock of mortgages that
can mitigate risks associated with the household stretch. For new mortgages, the debt service-toincome (DSTI) limits have been gradually tightened, and from 2013 new mortgages must take an
annuity or linear form in order for interest to be tax deductible. From 2014 onwards, the maximum
tax-deduction rate will be gradually reduced over 28 years. This will affect the stock of mortgages,
but the tax deduction will still be generous. Furthermore, new mortgages must be amortising in
order for the interest payments to be tax deductible.
Some improvements in the risk characteristics of new mortgages are already visible, for example
almost all new mortgages are now amortised. However, for the stock of loans, 21% are fully
amortising, 45% are partly amortising and 34% are not amortising at all, hence the households’
debt level is likely to be persistent for a long period of time. This is also because the measure
directly affecting the stock of loans, i.e. the reduction of the maximum tax deduction, will still be
generous after a long period of tightening. Moreover, in 2015 60.1% of households had bought a
house with a mortgage loan, which was one of the highest ratios in the EU (only Sweden has a
slightly higher ratio). The very high debt level in the Netherlands is partly explained by this very high
home-ownership ratio. This ratio has been increasing gradually for years, resulting in an increase in
households’ exposure to risks related to the real estate market.
While the measures taken for the household stretch are appropriate, they may not be sufficient to
fully address the identified vulnerabilities as they are only being gradually phased in and their
calibration will not be very constraining even after full implementation.

Collateral stretch
Risks related to the collateral stretch are also elevated. The loan-to-value ratios are among the
highest in the EU, both for the stock and for new mortgages (at 68% and 94% respectively).
Furthermore, approximately 25% of all mortgagors and 50% of mortgagors under 40 years old have
LTV ratios above 100%. As stated in the 2013 Eurosystem Household Finance and Consumption
Survey (the most recent data), every tenth mortgage holder in the Netherlands has negative wealth
– i.e. their debt is greater than their real and financial assets. Due to low amortisation rates, the
risks associated with high LTV ratios are likely to be persistent. If RRE prices were to fall again, the
LTV ratios would increase, which could lead to reduced private consumption affecting

145

The ratio of mortgage debt to GDP is 94.2%.

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macroeconomic and financial stability. However, a mitigating factor is that RRE prices appear not to
be overvalued according to the ECB model; likewise the PTI ratio appears muted at 85% (it was
100% in 2010). However, RRE prices were increasing by 4.4% annually in Q2 2016 and they are
closing the gap to the peak levels. However, this development is more pronounced in the major
cities than in the rest of the country. The authorities are gradually tightening the LTV limit, which
mitigates risks related to collateral stretch. By building up buffers upfront, an LTV limit will work as a
cushion before losses reach banks’ balance sheets or before private consumption is scaled back. A
lower initial LTV will also reduce the risk of a household becoming underwater if RRE prices fall.
The LTV limit is thus deemed to be the appropriate instrument to deal with risks related to collateral
stretch. However, the measure only affects new mortgages and the limit will still be high (100% in
2018) compared with other countries. There are no other measures in place for the collateral
stretch, and the policy stance is not expected to be sufficient in addressing the vulnerabilities in the
collateral stretch.

Banking stretch
Vulnerabilities related to the banking stretch are assessed to be more contained than for the two
other stretches. Risk weights for mortgage loans are close to the EU average, while the banks’
RRE exposures (mortgage loans to households, loans to construction companies and loans to real
estate companies) at the end of 2015 constituted 44% of total exposures. The ratio is close to the
historical average, but is above the euro area level of 38%.
Strong recourse facilities for lenders and strict personal bankruptcy rules may limit risks of direct
losses on mortgages for banks. However, the risks of indirect losses may be high, if households cut
consumption in order to service their high debt.
Moreover, stress tests indicate that the Dutch banks have sufficient capital in the event of strongly
adverse developments. The authorities have also addressed risks in the banking sector by
increasing capital buffers for the biggest banks during the period 2016-19, which should increase
the resilience of the banking sector further.
Regarding the capitalisation of the Dutch banking system, the CET1 ratio started to increase
slightly from mid-2015 and in Q1 2016 stood at 14.6% and was above the EU average of 13.9%.
The share of non-performing debt was 2.4% at the end of 2015 and was significantly lower than in
the EU (4.7%) or the euro area (5.6%). The Dutch banking sector’s reliance on market funding is
among the highest in the EU (in H1 2015 38% of funding came from market funding compared with
a weighted EU average of 12%), which makes it vulnerable to market shocks. Moreover, liquid
146
assets as a share of short-term liabilities amounted to 22% in H1 2015 which was lower than the
EU average of 40%.
Even though the risks in the banks may be limited, there could be increasing risks related to RRE in
the non-banking sector. Currently, around half of all new mortgages are provided by non-banks
(e.g. insurance companies). Selected macroprudential measures taken for loans (such as LTV

146

Liquid assets are defined as the sum of cash, holdings of MMF shares/units, holdings of debt securities with a maturity
below one year from euro area and domestic MFIs and the private sector, holdings of debt securities (total maturity) from
euro area and domestic general government, holdings of debt securities with a maturity below one year from the rest of the
world (all sectors) and inter-MFI loans (total maturity). This definition is used in the ECB report on “Analysis of the national
banking systems”.

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limits) also apply to loans provided by the non-banking sector. However, there is limited information
and analyses of the impact on financial stability of increased lending from the non-banking sector
are scarce.
Overall, the risks related to the banking sector seem limited and the measures are assessed as
appropriate and sufficient.

Table NL.3
Additional information on instruments and data available to micro and macro supervisory
authorities – The Netherlands
Do the macro and micro supervisory
authorities have the powers necessary to
implement/amend policy quickly and
effectively if/when required?

In the Netherlands, the Financial Stability Committee is the appointed macroprudential
authority. The committee identifies risks to financial stability and makes recommendations
with respect to these risks. Members of the committee are representatives of De
Nederlandsche Bank (DNB), the Authority for the Financial Markets (AFM) and the Ministry of
Finance. The Financial Stability Committee has no power to implement measures.
Measures are taken by DNB and the government, and many measures could be implemented
effectively and at short notice if required. DNB has the authority to set capital requirements for
banks, like the countercyclical capital buffer and other buffer requirements. LTV and DSTI/LTI
limits are set by the government in the Netherlands. The numerical value of the LTV limit is
set by a ministerial decree, which can be implemented at very short notice.

Do the macro and micro supervisory
No data issues that make the implementation of certain measures or the monitoring of risks
authorities have the necessary data to monitor difficult have been observed. However, the increasing mortgage lending by non-banks may
the risks and the impact of policy measures?
become an issue if it is harder to monitor and collect data from these institutions.
The effects of the measures taken have not been analysed and evaluated. However, this is
assumed to be due to the short period in which the measures have been in effect, rather than
a lack of data.

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Slovakia
Key points
The main vulnerability in the Slovakian housing market is related to the household stretch, in
particular rapid credit growth leading to increasing indebtedness of Slovakian households. Since
2011 there has been double-digit mortgage credit growth, which has accelerated since 2012 and in
June 2016 stood at 14% year-on-year. In 2004 credit for house purchases represented 8% of GDP,
which has increased to 25.6% of GDP in March 2016. This has been coupled with a strong
increase in household leverage (households’ total debt over financial assets), which is now 45%
compared with an EU average of 19%. By contrast, the debt-to-income ratio of Slovakian
households seems relatively low (at 46.7% in Q1 2016) compared with the EU average (of 108%).
However, the fast growth in household indebtedness, which is in part related to financial deepening
in Slovakia, has the potential to lead to a situation of excessive household indebtedness. Should
households become highly indebted, this could in turn lead to risks to the real economy related to
vulnerabilities in the RRE sector, and could thereby expose banks to possible direct and indirect
losses.
There are some additional factors that could amplify vulnerabilities related to household stretch.
First, around 20% of new loans are “top-up” loans, where borrowers – due to the low interest rate –
are able to increase the level of debt without increasing their debt servicing costs. Second, a high
share of mortgages is sensitive to interest rate changes, since around 83% of new loans had an
interest rate fixation period of between one and five years only. The strong economic outlook for the
Slovakian economy should mitigate these vulnerabilities to some extent.
Concerning the collateral stretch, following rapid credit developments, RRE price growth has picked
up since early 2015, following an earlier boom/bust cycle. However, RRE prices remain below their
peak (prices of flats are approximately 20% below their peak value of 2007). A few years ago a
loosening of lending standards had been observed, but they have been tightened following
recommendations by Národná banka Slovenska (National Bank of Slovakia – NBS) in October
2014. For example, the share of new loans with high LTV ratios is decreasing (see Chart SK.3).
Regarding the banking stretch, some RRE-related vulnerabilities have been identified. First, a
significant portion (45%) of Slovakian banks’ total loans are mortgage exposures (the euro area
average is 30%). Thus, if vulnerabilities were to crystallise in the RRE market (for example, an
interest rate rise that increases households’ debt service burden), this could potentially lead to
significant credit losses for the banks. Second, given already high and rising mortgage exposures
of banks, a potential cause for concern is that banks are compensating for lower mortgage interest
rate margins by increasing their mortgage volumes. This development requires close monitoring
despite the evidence that lending standards are now tightening.
As already mentioned, the Slovakian authorities implemented policy measures in October 2014 in
response to an observed loosening of lending standards. In particular, they made a
recommendation to ensure minimum lending standards including: limits on DSTI ratios, limits on
LTV ratios, maturity limits and amortisation rules. Since March 2016, following the implementation
of the Act on Housing Loans, the NBS has had a mandate to issue binding decrees imposing limits
on DSTI ratios, LTV ratios and mortgage maturities. It is currently preparing decrees to replace the
recommendations that have already been issued and will at the same time tighten some of the

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147

limits. The capitalisation of the banking sector in Slovakia has been increasing in recent years
and in Q1 2016 the sector-wide CET1 ratio was 15.7%, which is above the EU average.
Furthermore, Slovakian IRB banks have relatively high risk weights for RRE exposures, with
average risk weights standing at 17.2%. Moreover, the Slovakian authorities have taken measures
to mitigate risks related to banking stretch: the capital conservation buffer was set to 2.5% as of
1 October 2014; and the systemic risk buffer and O-SII buffer were activated with a combined value
up to 3% from 1 January 2018 after the phase-in.
In general, the Slovakian authorities show a high awareness of the strong cyclical credit
developments due to the current low interest rate environment. Consequently, the NBS decided to
increase the CCoB rate to 0.5% as of 1 August 2017.
Overall, given that the identified RRE-related vulnerabilities are assessed to be low although
increasing, the proactive policy stance in Slovakia is assessed as being appropriate and expected
to be sufficient to curb a future build-up in vulnerabilities. There is evidence that the policy
measures have already been quite effective, e.g. in stopping a decline in lending standards. In
addition, the move to transpose the current recommendations into decrees and to tighten some of
the limits should further increase their effectiveness. With respect to the banking stretch, the
increasing capital adequacy of the Slovakian banking sector, relatively high risk weights and the
active use of capital buffers including the CCyB are also considered to mitigate risks from banks’
exposures to the RRE sector.

Table SK.1
Summary assessment – Slovakia
Summary RRE risk
assessment narrative

Key risks are related to the collateral and household stretches
Rapid credit growth (credit for house purchases increased by 14% year-on-year in Q2 2016), albeit from low levels,
in Slovakia may signal rising vulnerabilities in the household stretch.
The credit growth is linked to financial deepening in Slovakia, but could potentially lead to a situation of excessive
household indebtedness.
There are some signs of household stretch: a high share of households is vulnerable to interest rate increases due
to short interest rate fixation periods.
Furthermore, RRE prices have been picking up since early 2015, which in combination with increasing debt
suggests increasing vulnerabilities in the collateral stretch. Overall, RRE prices do not appear to be overvalued.
There has been a tendency to relax lending standards in recent years, but this has somewhat reversed in response
to policy measures that have been implemented. There is a practice of “top-up financing” where the fall in the DSTI
ratio due to the low interest rates is being taken advantage of to increase the level of household debt.

Policy assessment given
risks

The policy stance is appropriate and expected to be sufficient
Overall, given that the identified RRE-related vulnerabilities are assessed to be low although increasing, the
proactive policy stance in Slovakia is assessed as being appropriate and expected to be sufficient to curb a future
build-up in vulnerabilities.
There is evidence that the policy measures have already been quite effective, e.g. in stopping a decline in lending
standards. In addition, the move to transpose the current recommendations into decrees and to tighten some of the
limits should further increase their effectiveness.

147

The October 2014 recommendation will be transposed into law in two ways: the mortgage loans part has been transposed
into the Act on housing loans (a new law); the consumer loans part is to be transposed into the Act on consumer loans (by
amendment). Both Acts give the NBS the mandate to issue binding decrees in the area of LTV ratios, DSTI ratios, etc. The
Acts will define the indicators (e.g. DSTI), but the level of the indicators will be specified in the decrees. The Act on housing
loans has been in force since 21 March 2016. The decree is under preparation and should be issued in the near future.
Additional measures will feature in this decree on housing loans. The amendment to the Act on consumer loans has been
prepared, but has not yet been approved. Once it is in force, the NBS will issue the corresponding decree on consumer
loans as well.

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Table SK.2
Summary of risks and policy measures – Slovakia
Household stretch

Collateral stretch

Banking stretch

Summary risk
assessment/main risks

Debt levels remain at intermediate
levels compared with other
countries, but the double-digit
mortgage growth (14% year-onyear in Q2 2016) contains a risk of
overheating.
A high share of mortgages is
sensitive to interest rate changes
due to relatively short interest rate
fixation periods (as of June 2016,
83% of new housing loans had a
fixation between one and five
years but the share of new loans
with interest fixation periods
shorter than one year is only 8%
and has decreased over the last
year).
An additional amplifying factor is
the widespread “topping-up” of
loans.

RRE prices have started to
increase of late. A number of
factors could lead to further
pressures on the prices: rapid
credit growth, low interest rates
and a positive economic outlook.
Currently, there does not appear to
be overvaluation in the Slovakian
housing market. Prices are still
below their pre-crisis peak.

Banks are compensating for lower
mortgage interest rate margins by
increasing volumes.
Bank exposures to mortgages are
increasing from already high levels
(currently 45% of total loans and
securities, against a euro area
average of 30%).
The banking sector capitalisation
ratio (CET1) in Slovakia stood at
15.7% in early 2016 which is
above the EU average (13.9%).

Summary of policy measures
(implemented, planned, under
consideration)

Implemented:
Recommendation in October 2014:
DSTI limit at 100%. The limit is
based on net income, includes an
interest rate stress element and
takes into account the number of
household members in
determining the household’s
expenses.

Implemented:
Recommendation in October 2014:
LTV ratio should not exceed
100%, with a given share of loans
above 90%.

Implemented:
Capital conservation buffer was
set to 2.5% as of 1 October 2014.

Recommendation in October 2014:
30-year maturity restriction for
mortgages (specific exemptions
are allowed). Loans with (partial)
deferred payment of interest or
principal should not be granted.

Planned:
Transposition of recommendations
into decrees with a tightening of
the limits.
Internal assessment of real estate
appraisals should be mandatory
and should meet certain minimum
qualitative requirements.

Systemic risk buffer and O-SII
buffer were activated with a
combined value up to 3% from 1
January 2018 after phase-in.
Countercyclical capital buffer is
currently at 0% and will be
increased to 0.5% as of August
2017.

Planned:
Transposition of recommendations
into decrees with a tightening of
the limits.
Assessment of policy
measures

Appropriate and expected to be
sufficient

Appropriate and sufficient

Appropriate and sufficient

Household stretch
The main concern for the household stretch is the increasing indebtedness of Slovakian
households. Since 2011 there has been double-digit mortgage credit growth, which has accelerated
since 2014 (in June 2016 the year-on-year growth in credit for house purchases was 14%; see
Chart SK.2). Credit for house purchases has increased from 8% of GDP in 2004 to 25.6% of GDP
in March 2016. This has been coupled with a strong increase in households’ leverage ratio
(households’ total debt over financial assets), which is now 45%, compared with an EU average of
19%. By contrast, the debt-to-income ratio of Slovakian households appears to be relatively low (at
46.7% in Q1 2016) compared with the EU average (of 108%). However, the fast growth in
household indebtedness, which is in part related to financial deepening in Slovakia, has the
potential to lead to a situation of excessive household indebtedness. Should households become
highly indebted, this could in turn lead to risks to the real economy related to vulnerabilities in the
RRE sector and could thereby expose banks to possible direct and indirect losses.
There are some additional factors that could amplify vulnerabilities related to household stretch.
First, around 20% of new loans are “top-up” loans, where borrowers – due to the low interest rate –
are able to increase their debt level without increasing their debt servicing costs. Second, a high
share of mortgages is sensitive to interest rate changes, since around 83% of new loans have an
interest rate fixation period of between one and five years only. The strong outlook for the
Slovakian economy should mitigate these vulnerabilities to some extent.

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The Slovakian authorities have issued a number of recommendations to address these
vulnerabilities, including: a DSTI limit of 100% (verified net income after living cost deduction),
which must include an interest rate stress element if the rate is not fixed until maturity; and a
maturity limit of 30 years. The DSTI calculation methodology already includes a buffer for a
potential interest rate increase by 2 p.p.
Furthermore, the Slovakian authorities are planning to take additional tightening measures when
148
the current recommendations have been transposed into decrees. The decree has been
prepared in cooperation with the banking association; therefore, banks are aware of the tightening
of these measures. Moreover, the plans to tighten the measures were also publicly announced in
the May 2016 Financial Stability Report (without any specific details however).
Given that the identified vulnerabilities in the household stretch are assessed to be low but
increasing, and that the implemented and planned measures are expected to curb the build-up of
vulnerabilities in the household stretch going forward, the policy stance is deemed as appropriate
and expected to be sufficient.

Collateral stretch
For the collateral stretch, some build-up of vulnerabilities has been identified. Despite strong
mortgage credit growth since 2011, RRE price growth has been relatively flat over the past years.
Lately, however, RRE prices have started to pick up (4.7% year-on-year growth in Q2 2016).
Overall, there does not appear to be a general overvaluation of RRE prices in Slovakia (according
to real estate price valuation models, they are undervalued in Slovakia for the moment). For
instance, compared with income and rents, RRE price growth appears to have been relatively
muted (the PTI index was 94% in Q1 2016 and has increased by 1.6 p.p. annually; meanwhile the
PTR index was 105% in Q1 2016 and has increased by 4.8 p.p. annually) and remains significantly
below the peak. Historically, RRE prices in Slovakia have been relatively volatile, which is mainly
due to the fact that it is a relatively small market in terms of the number of properties compared with
other EU countries.
There are a number of factors that may lead to a build-up of vulnerabilities in the collateral stretch.
In particular, rapid mortgage credit growth, supported by a positive macroeconomic outlook and the
low interest environment, which has led to a significant decline in mortgage interest rates (the
largest drop in any EU country last year), are likely to lead to further pressures on RRE prices. In
addition, there are signs of a potential construction boom in Bratislava, although domestic
construction production contracted in real terms in the first part of 2016. According to the European
Commission, RRE-related investments amounted to 6% of GDP in 2013.
As for the collateral stretch, the Slovakian authorities have taken a range of measures through
recommendations. They have issued a recommendation that the LTV ratio on new loans should not
exceed 100%, with a given limited share of new loans having an LTV ratio above 90%. They also
advised banks to maintain a prudent approach when appraising real estate collateral: internal
assessment of real estate appraisals should be mandatory and should meet high qualitative

148

See above fn. 147 for further details.

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requirements. The NBS is working to transform the LTV measure from a recommendation into a
149
decree and there are plans to tighten the limit.
In the recent years there appears to have been a relaxation of lending standards. However,
subsequent to the NBS recommendations in October 2014, lending standards appear to have been
tightening. For example, the share of new loans with an LTV ratio above 90% has decreased,
which is likely due to the LTV limit.
Given the level of identified vulnerabilities in the collateral stretch and that the taken and planned
measures are expected to prevent an unsustainable build-up of vulnerabilities going forward, the
measures are assessed as being appropriate and sufficient, in particular since lending standards
now appear to be tightening and the share of new loans with high LTV ratios is decreasing.

Banking stretch
Regarding the banking stretch, some RRE-related vulnerabilities have been identified. First, a
significant portion of Slovakian banks’ total loans are mortgage exposures (45%), which is higher
than the euro area average (30%). Additionally, general exposure to the real estate sector (i.e.
mortgage loans and loans for real estate and construction activities) at the end of 2015 constituted
54% of all loans. Both these measures for Slovakia are among the highest in the EU. Thus, if
vulnerabilities were to crystallise in the RRE market (for example, an interest rate rise that
increases households’ debt service burden), this could potentially lead to significant credit losses
for the banks. Second, given already high and rising mortgage exposures of banks, a potential
cause for concern is that banks are compensating for lower mortgage interest rate margins by
increasing their mortgage volumes. This development requires close monitoring despite evidence
that lending standards are now tightening.
The Slovakian authorities have taken measures to mitigate risks related to banking stretch: the
capital conservation buffer was set to 2.5% as of 1 October 2014; the systemic risk buffer and O-SII
buffer were activated with a combined value up to 3% from 1 January 2018 after phase-in; and the
NBS decided to set the countercyclical capital buffer rate to 0.5% as of August 2017.
The banking sector capitalisation ratio (CET1) in Slovakia has been increasing in recent years and
was 15.7% in Q1 2016, above the EU average of 13.9%. The liquidity position of banks in Slovakia
is strong: short-term liabilities are quite well covered by liquid assets relative to banking systems in
other EU countries, banks’ dependence on market funding has been decreasing and customer
deposits constitute a greater share of their liabilities. Furthermore, the average risk weights for
Slovakian IRB banks on RRE exposures were 17.2% in June 2016, which is above the EU average
of 16%. The combination of limited vulnerabilities related to the banking stretch, comparatively high
capital adequacy and RRE risk weights and the banking policy measures that have been
implemented suggests that the policy stance is appropriate and sufficient for the banking stretch.

149

Ibid.

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Table SK.3
Additional information on instruments and data available to micro and macro supervisory
authorities – Slovakia
Do the macro and micro supervisory
authorities have the powers necessary to
implement/amend policy quickly and
effectively if/when required?

Overall, the Slovakian authorities can rely on a comprehensive set of powers:
a) The NBS has responsibility for microprudential supervision and macroprudential
supervision according to the Act on Supervision.
b) The NBS has a mandate to set capital buffers according to the Act on Banks.
c) The NBS has a mandate to set borrower-based measures on mortgages (e.g. LTV ratios,
DSTI ratios, amortisation, etc.) according to the Act on Housing loans (together with the
transposition of the EU Mortgage Credit Directive).
Borrower-based measures for housing loans are currently in the Act on Housing loans, but
they are not yet available for other consumer loans. The legislation process giving the NBS
the same powers in the field of consumer loans is in its final stages, but is not yet complete.
For housing loans, the Recommendation on lending standards has been transformed into law
and has given the NBS the mandate to issue binding decrees in the area of LTV ratios, DSTI
ratios, etc. (as explained in footnote 147).

Do the macro and micro supervisory
There is good data coverage on average LTV values and the LTV distribution for new loans,
authorities have the necessary data to monitor although long time series are not yet available. The data originate from banks and cover all
the risks and the impact of policy measures?
loans provided in the banking sector (not just a sample). The same data are available for
mortgage maturities.
A solid information base on DTI values is missing: the NBS knows banks’ minimum DTI
requirements but does not know the actual DTI ratio on issued loans.

Annex with charts
Chart SK.1
RRE price changes

Chart SK.2
Share of mortgage loans in the total loan
portfolio

(index: 2010 = 100)

(percentage)

nominal HPI
real HPI
50

130

45

120
40

110

35
30

100

25

90

20
15

80

10

70

5

60
2005

2007

2009

2011

2013

2015

Source: OECD.

0
2006

2008

2010

2012

2014

2016

Sources: ECB SDW (money, credit and banking statistics) and ESRB
calculations.

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Chart SK.3
Share of new loans with a high LTV ratio
share of new loans with LTV between 90% and 99%
share of new loans with LTV between 99% and 100%
recommended limit
30

25

20

15

10

5

0
Q4 2014

Q1 2015

Q2 2015

Q3 2015

Q4 2015

Q1 2016

Source: NBS.
Note: 2014Q4 = November and December 2014.

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Sweden
Key points
The main RRE-related vulnerabilities in Sweden are the rapidly growing RRE prices which appear
to be overvalued, and high and increasing indebtedness especially among some groups of
households. These are related to both the household and collateral stretches.
The rapid increase in the debt-to-income level continued. The 2016 Mortgage Survey of
Finansinspektionen (the Swedish Financial Supervision Authority, hereafter referred to as FI)
shows that the DTI ratio (based on disposable income) for households with new loans increased to
406% in 2015, from 387% in 2014. Furthermore, a high number of households with new loans have
very high DTI levels (approximately 35% of households have a DTI level of more than 450% and
150
about 7% has a DTI ratio above 750%). Loans to households for house purchases grew by 8.7%
annually in June 2016.
There has been a substantial and prolonged rise in RRE prices. RRE prices have been increasing
since the mid-1990s, except for the period 2007-12 when house prices fell or were flat (see Chart
SE.3). In the last years, RRE prices have been increasing faster than income for both apartments
and houses (see Chart SE.1). However, during the last six months RRE price growth has slowed
down markedly. This could be a minor correction of the prices or it could be the beginning of a
downturn in the housing market. Still, RRE prices appear to be elevated: the ECB estimates the
Swedish housing market to be overvalued by 24%, whereas the IMF methods suggest an
151
overvaluation of between 5.5% and 12%. Furthermore, the price-to-income ratio is one of the
highest in Europe.
As for other countries, the drivers of the rapid increase in real estate prices and high household
indebtedness are demographics, urbanisation, a regulated rental market, strong income growth,
low interest rates and lower taxation of home ownership. Supply-side restrictions in the form of a
shortage of skilled labour and a lack of access to land in attractive areas have also contributed to
these dynamics.
With a household debt-to-GDP ratio of 84%, Swedish households are among the most indebted in
Europe and household indebtedness is increasing. The dynamics of LTV ratios are, however, more
muted and they have fallen from 67.5% in 2009 to 61% in 2015, partly driven by the introduction of
the LTV ceiling of 85% in 2010, the rise in RRE prices and increases in amortisation during the
period. A rising share (currently around 65%) of households is amortising the mortgages. The
number of amortising households is set to increase further due to the amortisation requirement that
came into force on 1 June 2016. This is expected, to some extent, to dampen the share of
households with new loans with high DTI ratios. The introduction of this measure could be
responsible for the recent developments in RRE prices.
For the banking stretch, the Swedish authorities have taken several measures. These include a risk
weight floor of 25% for mortgages, a 5 p.p. additional capital requirement for the four largest
Swedish banks (which account for the vast majority of the mortgage market in Sweden) and a
countercyclical capital buffer (currently set at 2%). The banking sector is well capitalised and
profitable compared with European peers (see Chart SE.7). Still, Sveriges Riksbank recommends a

150

The Swedish Mortgage Market 2015, Finansinspektionen, April 2015.

151

Turk (2015) as above fn. 23.

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further tightening of capital requirements in order to strengthen the resilience of the banking
system. Banks’ lending standards appear to be high (in credit decisions an average interest rate of
6.5% is typically factored in). However, funding risks from high reliance on market funding, in
particular in foreign currency, is a source of vulnerability for the Swedish banking system (52% of
the banking system’s total liabilities are market funding and 37% of the liabilities are in foreign
152
currency ). There is, however, an LCR requirement in place both in aggregate and separately in
US dollars and euros.
Households are resilient in FI’s stress tests, have high saving rates and have large asset holdings.
Nevertheless, a large proportion of households’ assets are tied up in pension schemes and/or
residential real estate, which may hamper their use as liquidity sources and eventually amplify a
shock to the real estate sector. Also, the distribution of these assets is not known. Due to the
banking measures taken, and since households seem to have a sufficient margin for servicing their
debt, the banking system seems to be fairly resilient to direct shocks from the mortgage market.
Due to these factors, the main identified risk is mostly related to the indirect channel and secondround effects. High indebtedness combined with large financial assets mean that households’
balance sheets are large and vulnerable to correlated asset price shocks, pointing to substantial
macroeconomic risks. The interaction between increases in debt-to-income ratios and RRE prices
implies that a shock to the economy (e.g. a drop in incomes or RRE prices, or increasing interest
rates) could force households to cut back on consumption. This could be driven either by a need of
households to service their debt (despite their margin) or by general wealth effects. If many
households were to be forced to reduce consumption, this would be expected to have a significant
negative effect on the overall economy. This, in turn, may cause second-round effects by impacting
the wider non-financial sector and may result in losses to the banks. However, the Riksbank’s and
FI’s joint stress tests indicate that banks are resilient enough to withstand a severe macroeconomic
deterioration. However, the Riksbank and FI consider that it is difficult to draw conclusions
regarding the capital requirements of the Swedish banking system on the basis of a single stress
153
test.
The introduction in 2010 of an 85% limit on the loan-to-value ratio for new mortgages and an
amortisation requirement in 2016 are expected to address the build-up of further vulnerabilities to
some extent. While the current policy measures are appropriate given the nature of RRE
vulnerabilities in Sweden, they may not be sufficient to fully address them. Given that the measures
apply only to new housing loans, it will take time for the vulnerabilities related to the level of
household indebtedness to substantially decrease. Also, the mandate of FI with respect to some
measures (e.g. an LTI cap) remains unclear, which may impair its ability to act.

152

Analysis of the national banking systems, ECB, 2015.

153

See Stability in the Financial System, 2015:2, Finansinspektionen, and Financial Stability Report, 2015:2, Sveriges
Riksbank.

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Table SE.1
Summary assessment – Sweden
Summary RRE risk
assessment narrative

Key risks are related to the collateral and household stretches
The main vulnerabilities are considered to be the rapidly increasing RRE prices which appear to be overvalued,
and high and increasing indebtedness especially among some groups of households. In addition, if risks were to
materialise, there could be potential spillover effects on other countries in the Nordic-Baltic region.
High and rising debt-to-disposable income ratio for households with new loans (406% in 2015, up from 387% in
2014).
Credit growth has been rapid (loans to households for house purchases have increased by 8.7% year-on-year in
June 2016).
A prolonged and continuing increase in RRE prices (by 12% in 2015), which has however slowed down during the
last six months.
RRE prices are, according to the ECB model, the most overvalued in Europe, though the IMF model shows less
overvaluation.

Policy assessment given
risks

The policy stance is not expected to be sufficient for the collateral and household stretches
The current policy measures are appropriate given the nature of RRE vulnerabilities in Sweden, but they may not
be sufficient to fully address them.
Given that the measures apply only to new housing loans, it will take time for the vulnerabilities related to the level
of household indebtedness to substantially decrease.
The lack of tools is related to the fact that FI’s mandate remains unclear with respect to some measures.
Furthermore, the high and somewhat overvalued RRE prices have not been directly addressed.

Table SE.2
Summary of risks and policy measures – Sweden
Household stretch

Collateral stretch

Banking stretch

Summary risk assessment/main
risks

Debt-to-disposable income ratios
have been rising from an already
high level (see Chart SE.2). In
particular, DTI ratios have been
rising for households with new
mortgages (from 387% to 406%
between 2014 and 2015).
There have been some significant
increases in amortisation rates in
the last few years, but still 32% of
new mortgages and 35% of existing
mortgages are not amortised. The
amortisation requirement is
expected to increase the share of
new mortgages being amortised.

RRE prices have been rising
rapidly, both in absolute terms (see
Chart SE.3) and relative to income
(see Chart SE.1). RRE prices are
estimated to be overvalued by 24%
(ECB) or by between 5.5% and
12% (IMF). Therefore, the risk of a
price correction is present.
Mitigating factors are the decrease
in the LTV ratio, which has fallen
from 68% in 2009 to 61% in 2015,
and the recent slowdown in RRE
price growth.

The Swedish banking sector is well
capitalised and profitable compared
with European peers, and lending
standards appear prudent.
The Swedish banks have high riskweighted capital ratios.

Summary of policy measures
(implemented, planned, under
consideration)

Implemented:
Amortisation requirement: since 1
June 2016 all new household loans
have to be amortised by 2% of the
original debt burden yearly if the
LTV is above 70% and by 1% if the
LTV is in the 50-70% range.

Implemented:
An LTV cap at 85% since 2010

Implemented:
25% risk weight floor on mortgages
since 2013-14
5 p.p. additional capital requirement
for systemic banks
An LCR of 100% in aggregate and
separately in USD and EUR since
2013

Under consideration:
An LTI cap has been discussed but
this measure, as well as debt
service requirements, are currently
not under the FI’s mandate.

Assessment of policy measures

Appropriate but not expected to
be sufficient

A CCyB set at 2% effective as of
March 2017 (The current effective
CCyB rate is 1% as of September
2015 and 1.5% as of June 2016.)
Appropriate but not expected to
be sufficient

Appropriate and sufficient

Household stretch
Swedish households are highly indebted, and their indebtedness is continuing to rise; the DTI ratio
for households with new loans increased to 406% in 2015 from 387% in 2014 (see Chart SE.2).
With regard to RRE risks, Swedish households, banks and the overall economy are primarily
exposed to indirect effects. The indirect effects are likely to be driven by decreases in consumption,

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if households are forced to cut back in order to service their debt, or through general wealth effects.
This has been the case during RRE-related crises in other countries (see Chart SE.4), where
households in countries with high debt levels reduced their consumption the most. This risk could
materialise in an adverse scenario relating to increases in interest rates or decreases in incomes.
There are several underlying drivers that have led to Swedish households’ high indebtedness. One
major driver is the regulated rental market, which forces some households to choose owneroccupied housing rather than renting, thus increasing the aggregated debt burden of the household
sector. However, the home-ownership ratio in Sweden is still below the EU average (70% versus
the EU average of 76%), even though it has risen. Other structural factors include a tax system
favouring owner-occupied housing (interest expenses are tax deductible and the property tax was
abolished and replaced with a low municipality fee) and the prevalence of variable rate mortgages.
The proportion of households with new loans amortising their debt has been steadily increasing
from 42% in 2010 to 68% in 2015. However, 32% of households with new loans do not amortise,
which in combination with the high indebtedness still constitutes a vulnerability, mainly to the real
economy through possible effects on consumption. However, amortisation rates are higher for
households with high LTV ratios (approximately 90% of those households with an LTV above 70%
amortise their mortgages). Second-round effects affecting the banking system are a possibility, but
the joint Riksbank/FI stress tests show banks to be highly resilient. Given the amortisation rate, the
identified vulnerabilities are not likely to decrease quickly, even if the further growth of loans is
subdued.
The situation is somewhat mitigated by the high levels of wealth and savings of households. In
aggregate, households hold substantial assets. However, since a large proportion of these assets
is tied up in pension schemes and/or residential real estate (see Chart SE.5), they cannot be
liquidated easily and the distribution of household assets among households is not known. Swedish
household leverage (debt over financial assets) is lower than the EU average and falling. This is
linked to the fact that Swedish households save a considerable amount of their disposable income
(16% in 2015). This is partly due to very high mandatory pension savings, but even when stripping
those out, a saving rate of 8% is still high. The high saving rate could provide a cushion which
would to some extent mitigate a sharp decrease in consumption.
Banks’ lending standards on mortgages are high in Sweden and have tightened slightly over the
last few years. For example, the banks ensure that households are able to handle higher interest
rates by using high imputed rates of interest. The 2016 Mortgage Survey conducted by FI shows
that the average imputed rate of interest for 2015 was around 6.5%, which can be compared with
the average mortgage rate in the sample of 1.7%.
In addition, FI conducts regular stress tests of households in order to study their resilience to
financial shocks. In the stress tests, FI estimates how the households’ payment ability would be
affected by rising interest rates, unemployment or a drop in the value of their home. The stress
tests show that most households that have taken out new mortgages have a sufficient margin to
handle negative scenarios such as higher interest rates, higher unemployment or declining RRE
prices. Even in the event of severe stress, few households experience problems with their
payments. The stress tests show that, if interest rates were to increase by 5 p.p., only 3.5% of new
borrowers would no longer have a surplus, forcing them to reduce their costs (e.g. buy a more
affordable home). The stress tests also show that household resilience has increased compared
with earlier years. Hence, the stress tests suggest that households’ need to liquidate assets even in
a stressed scenario would be limited.

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FI recently introduced an amortisation requirement whereby loans issued from 1 June 2016 must
be amortised at a rate of 2% of the original debt burden yearly for LTV ratios above 70% and at a
rate of 1% for LTV ratios in the 50-70% range. This is expected to enhance the resilience of
households by increasing the share of households amortising their mortgage debt and by making
households with a high LTV ratio amortise their debt more quickly. The amortisation requirement
could also be expected to have some impact on the share of high DTI households. This is because
an increase in amortisation will limit the size of the loan a high DTI household is eligible to borrow,
as banks require their borrowers to have sufficiently high net disposable incomes (post costs and
amortisation) to service the debt. The newly introduced amortisation requirement was preceded by
a prolonged discussion, which led banks to gradually tighten their lending standards (e.g. reducing
LTV ratios and increasing amortisation rates).
A loan-to-income (LTI) cap is also being considered by FI, but FI does not appear to have the legal
powers to introduce this measure (see Table SE.3). Some banks have also started to impose
voluntary LTI caps. Despite this, household credit has grown faster than disposable income over
the last few years. Loans to households for house purchases grew by 8.7% annually in June 2016,
a development which raises concerns.
The measures taken apply only to new housing loans, meaning that it will take time for the
vulnerabilities related to the level of household indebtedness to substantially decrease. The
amortisation requirement will affect new loans and is therefore an appropriate measure. Addressing
the level of indebtedness is difficult for legal and practical reasons. However, vulnerabilities exist
and appear to be rising, and the current policy stance is not expected to change this over the
medium term. Hence, the vulnerabilities may not be sufficiently addressed by the policy stance. The
lack of tools is also related to the absence of a clear mandate of FI regarding certain tools (such as
LTI limits).

Collateral stretch
Swedish RRE prices appear to be high. Prices have risen steadily since the early 1990s, with the
exception of the period 2007-12 when RRE prices fell or stayed level (see Chart SE.3). However,
price developments have slowed down in the last six months. It is difficult to say whether this is just
a minor correction or the beginning of a housing market downturn. As in many other countries, the
price increases have been particularly pronounced in major urban areas. For the whole of Sweden,
RRE prices have doubled since the 1990s, but in major cities (like Stockholm, Göteborg, Malmö
154
and Uppsala) they have increased by 300-400%. These developments have led to a situation
where the price-to-income ratio is high by historical comparison (see Chart SE.1). Furthermore, a
material overvaluation is suggested by the ECB (24%). However, other methods suggest only a low
to moderate overvaluation (the IMF suggests an overvaluation of between 5.5% and 12%). The
high and overvalued RRE prices suggest that a cooling-down of price developments is warranted,
but could also suggest that a larger downturn is possible.
In addition to the drivers mentioned in the household stretch section, structurally low construction of
housing has been a major driver of rising RRE prices. A shortage of skilled labour and a lack of
access to land in attractive areas have caused supply to consistently fall short of demand for the

154

“Sweden: Selected Issues”, IMF Country Report No. 15/330, December 2015.

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last decade (see Chart SE.6). At the same time, demand has been fuelled by high net immigration
and rapid urbanisation. Rules largely prohibit housing speculation and there is virtually no buy-to-let
market in Sweden. These factors should all support RRE prices to some extent, even in a
downturn.
Swedish households are overall assessed to be highly resilient in stress tests carried out by FI. For
example, if the interest rate increases by five percentage points at the same time as RRE prices
decline by 20%, around 1% of households would have a deficit as the LTV ratio would exceed
100%. If prices were to fall by 40%, the corresponding figure would instead be 2.5% of households.
The LTV cap of 85%, introduced in 2010, is considered an appropriate policy measure to address
this vulnerability, since it has halted the trend of rising average LTV ratios for new borrowers.
However, given the high levels and possible overvaluation of RRE prices, the LTV measure may
not be sufficient in neutralising the vulnerabilities in the collateral stretch.

Banking stretch
Swedish households have a high ability to service their debt and the Swedish banking system is
profitable and well capitalised compared with EU peers (see Chart SE.7). Loans are of the fullrecourse type and credit losses on household loans have, during previous real estate crises, been
low. The risk of direct losses from a real estate-related crisis should never be completely dismissed;
when assessments and stress tests are done in situations with lending booms and increasing RRE
prices, they tend to generally underestimate the real size of non-performing assets. An example is
the case of Spain, which is different from that of Sweden in many ways, where the average nonperforming loan ratio was 0.6% for lending to the private sector at end-2006, but had increased to
14% by the end of 2013.
Funding risks from reliance on market funding (market funding in the Swedish banking system is
155
52% of total liabilities, against an EU average of 12% ), in particular in foreign currency (37% of
156
funding is in foreign currency, against an EU average of 12% ), is a source of vulnerability for the
Swedish banking system. In addition, the banking system is highly concentrated and sizeable in
relation to the overall economy (in Sweden the total banking assets-to-GDP ratio is 402%, against
157
an EU average of 284% ). The interconnectedness between banks across the Nordic-Baltic
region implies that there could be significant cross-border spillovers to banks from RRE-related
difficulties in any of the countries in the region.
Against this background, FI has set high capital and liquidity requirements for Swedish banks in
general and the four major banks in particular. The measures addressing the banking stretch are
comprehensive and include both general and targeted measures (including liquidity requirements).
These measures (see Table SE.2) are assessed as being sufficient in addressing the banking
stretch in Sweden.

155

Analysis of the national banking systems, ECB, 2015.

156

Ibid.

157

Ibid.

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Table SE.3
Additional information on instruments and data available to micro and macro supervisory
authorities – Sweden
Do the macro and micro supervisory
authorities have the powers necessary to
implement/amend policy quickly and
effectively if/when required?

Finansinspektionen (FI) is the macroprudential authority. It has a clear mandate to decide on
and implement all of the macroprudential tools provided for in the CRR/CRD. FI has been
using these available tools in combination with other tools falling under its microprudential and
consumer protection mandates.
A judicial challenge last year regarding the planned amortisation requirement showed,
however, that the mandate of the institution is unclear with regard to national measures
(amortisation requirement, LTI cap, etc.) addressing risks to macroeconomic stability.
Reflecting this uncertainty, the law had to be amended in order for FI to introduce the
amortisation requirement. In March 2016 the Swedish Parliament approved the law
amendment that enabled FI to introduce the amortisation requirement. Other measures such
as the discussed LTI cap are currently not within FI’s mandate. FI is therefore working
towards obtaining a wider mandate, which also includes the use of national measures
addressing risks to macroeconomic stability, in addition to the measures provided for in the
CRR/CRD.
Furthermore, FI cannot introduce measures that target the stock of loans; only new loans can
be addressed.

Do the macro and micro supervisory
In general, data are available, but information on households’ assets and savings is limited.
authorities have the necessary data to monitor Since the abolishment of the wealth tax in 2007, these data have only been available in
the risks and the impact of policy measures?
aggregate form. Therefore, it is not possible to gauge whether the most indebted households
are also the households with the highest savings.

Annex with charts
Chart SE.1
Swedish residential real estate prices
relative to disposable income

Chart SE.2
Household debt in Sweden

(index: Q1 2005 = 100)

(percentage of disposable income)

houses
apartments

200

200

180

180

160

160

140
140

120
120

100

100

80

80
60

60

40

40

20

20

0
1986

1991

1996

2001

2006

2011

Sources: Statistics Sweden and Valueguard.

0
1970 1975 1980 1985 1990 1995 2000 2005 2010

Sources: Statistics Sweden and Sveriges Riksbank.

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Chart SE.3
Real property price index in Sweden
(index: Q1 2000 = 100)

200
180
160
140
120
100
80
60
40
20
0
1987 1990 1993 1996 1999 2002 2005 2008 2011 2014

Sources: Statistics Sweden and Sveriges Riksbank.
Notes: Deflated with CPIF (consumer price index with a fixed interest
rate). Refers to developments in prices of single‐family houses.

Chart SE.4
The relationship between the debt-to-income ratio and consumption growth, 2007-12
(x-axis: households debt ratio 2007; y-axis: adjusted consumption, (percentage))
10
CZ

8

MX

6

AU
SK

HU

4

CA

BE
FR
FI
AT DE

2
SI

US
KR
SE

0

JP
IT

-2

EE

PT

NO

IE
NL

ES

-4

UK
CH

-6
DK
-8
0

50

100

150

200

250

300

350

400

Sources: OECD and Sveriges Riksbank.
Note: Adjusted consumption growth has been calculated as actual consumption growth minus contributions from growth in the debt ratio, the current
account and consumption. For further information, see Flodén, M., “Did household debt matter in the Great Recession?”, 2014.

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Chart SE.5
Household assets and debt
(percentage of disposable income)
total assets
real assets

financial assets
debt

700
600
500
400
300
200
100
0
1980

1990

1985

1995

2000

2005

2010

2015

Sources: Statistics Sweden and Sveriges Riksbank.

Chart SE.6
Housing construction and population changes in Sweden
one- or two-dwelling buildings
multi-dwelling buldings

population change

120.000

100.000

80.000

60.000

40.000

20.000

0
1958

1963

1968

1973

1978

1983

1988

1993

1998

2003

2008

2013

Source: Statistics Sweden.

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Chart SE.7
Capital ratios by banks' home country
(June 2015)
fully loaded CET1
CET1

tier 1
total

25%

20%

15%

10%

5%

0%
LV

AT

MT

IT

PT

UK

ES

NO

FR

PL

EU

HU

NL

CY

DE

DK

BE

IE

LU

SI

SE

FI

Source: 2015 EU-wide transparency exercise: aggregate report, EBA, 2015.

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The United Kingdom
Key points
There is currently a high degree of uncertainty about the medium-term outlook for the UK housing
market. However, from a macroprudential perspective, there appear to be risks under different
housing market scenarios – either through the crystallisation of accumulated vulnerabilities,
particularly related to household indebtedness and the interaction with elevated RRE prices, or
through the further build-up of vulnerabilities.
The uncertainty following the UK’s referendum on European Union membership on 23 June 2016
may have caused a turning point in the UK residential real estate market. The result of the UK
referendum on EU membership on 23 June 2016 initially had a significant market impact and the
full implications for the UK economy are still uncertain. Before the vote, the main vulnerabilities
associated with residential real estate in the UK related to the high level of household indebtedness
in combination with RRE prices which had been rising for several years, and the potential for these
to reinforce each other.
Following the June referendum, the Bank of England and some international institutions revised
down the outlook for the UK economy and housing market. If those forecasts prove to be correct, it
would slow the pace of build-up in mortgage debt and therefore reduce vulnerabilities in the
medium term. However, the probability of risks through these channels materialising may have
increased. If they were to materialise, the associated negative household income and wealth
effects (e.g. if households need to reduce consumption in order to service their mortgage loans)
may reinforce the initial shock, with negative direct and indirect effects on financial stability.
Conversely, it is also possible that the slowdown in the housing market could prove to be temporary
and, after a pause, RRE prices, mortgage approvals and household debt could begin to grow
again. In this scenario, vulnerabilities related to residential real estate would continue to rise.
The Financial Policy Committee (FPC), the Prudential Regulation Authority (PRA) and the Financial
Conduct Authority (FCA) took a number of policy measures targeted at RRE vulnerabilities before
the referendum. These led to improvements in mortgagor resilience and have ensured a rising
capitalisation of the banking system. On 3 August the Bank of England’s Monetary Policy
Committee (MPC) introduced a package of measures to support the economy (including an interest
rate reduction and measures to ensure that lower rates pass through to the real economy). These
measures should also support mortgagors and the housing market, and might lower the risk of
crystallisation of the above-mentioned vulnerabilities.
Overall, the UK residential real estate market is potentially at a turning point. Given the uncertainty
of the implications of the UK’s referendum on EU membership, it is not yet possible to judge
whether the vulnerabilities that had accumulated will now begin to crystallise or whether, in time,
they might instead continue to grow. The appropriate policy response is likely to differ between
these two scenarios. Therefore, it will be important for the UK authorities to monitor developments
closely and adjust macroprudential policy in light of these. Looking ahead, it will be necessary to
ensure that any adjustment in the housing market proceeds at an appropriate pace and that new
imbalances do not emerge.

Situation before the UK’s referendum on EU membership in June 2016
The household stretch assessment is primarily based on the relatively high debt levels in the UK
household sector. However, it also takes into account the debt dynamics, distributional aspects and
interactions with other stretches, in particular the collateral stretch.

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The aggregate household debt-to-income ratio is historically and internationally high (130% as at
Q1 2016) and the household debt-to-GDP ratio was the fifth highest in the EU in Q2 2016.
However, the aggregate household debt-to-income ratio fell between 2008 and 2012-13, and has
remained flat since then. And, as discussed in Section 2.1.2, there is considerable uncertainty
158
around the sustainable level of household debt. In the UK, around half of mortgagors are on
floating rate contracts, which make them vulnerable to rises in interest rates, but can also be a
mitigating factor if interest rates fall in a stress. The stock of interest-only loans to owner-occupiers
fell from 31% in Q3 2013 to 23% in Q1 2016 (this also has implications for the collateral stretch).
The proportion of households that own their own home and the proportion that have mortgage debt
is in line with the EU averages (in 2016, 30% of households were mortgagors). Cross-country
evidence indicates that homeowners, particularly those which are more highly indebted relative to
their income, respond to interest rate and income shocks by reducing consumption, thus creating a
potential risk channel to the economy due to household indebtedness.
Although new borrowing at high loan-to-income ratios (i.e. with a loan-to-income ratio at or above
4.5) has declined, it remained at around 9% as at Q1 2016 (7.6% as at Q2 2015). And, since the
financial crisis, there has been a decrease in the share of very highly indebted households in the
stock. The proportion of households with a total debt-to-income ratio greater than 5 has fallen from
3.3% in 2011 to 1.6% in H1 2016. An additional 5.5% of households have a total debt-to-income
ratio of between 3 and 5, down from 6.6% in 2011. This is a positive development and should
reduce the risk of vulnerabilities that may arise due to income and interest rate shocks.
Risks related to collateral stretch have been a growing vulnerability: RRE prices had been growing
rapidly from already high levels and have been decoupling from rent and income growth rates. The
159
recent IMF Article IV consultation discussed that RRE price growth has been more than three
times income growth recently and the price-to-rent ratio has risen steeply since late 2012 (the index
value was 111% in Q1 2016 with a base year of 2010; see Table C.1 in Annex C). The nominal
RRE price level exceeded its pre-crisis peak in 2015 – although, of course, this is in the context of
much lower long-term interest rates (and, in real terms, RRE prices remain below pre-crisis peaks).
RRE price growth was rapid at 6.4% year-on-year to July 2016; however, RRE price growth has
been slowing recently (on a three month-on-three month annualised basis, RRE price growth has
fallen from a recent peak of 9% in February to 5% in July).
Mortgages in the UK generally have somewhat high LTVs at origination relative to other countries
(at present, the median LTV is around 75% for the flow of mortgages to owner-occupiers; see Table
C.1 in Annex C). However, the majority of loans to owner-occupiers amortise over time and thus
data on the distribution of LTVs in the stock of mortgages show that the share of mortgages with an
LTV higher than 75% is only around 16%, and only 3% have an LTV greater than 90% (Q4 2015).
Buy-to-let (BTL) lending has been the biggest contributor to net mortgage lending growth, with BTL
making up 17% of the flow of gross mortgage lending. Although BTL investors typically borrow at
lower LTVs at origination, their mortgages tend to be on interest-only terms, meaning that the loan
value can remain significant on lenders’ balance sheets.

158

For example, the structural fall in interest rates in recent decades suggests that a higher debt level than previously may be
sustainable. And the sustainable level of indebtedness is also likely to vary between countries.

159

2016 Article IV Consultation Concluding Statement of the IMF Mission.

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Despite the growing vulnerabilities for a collateral stretch and the fact that mortgages account for
approximately two-thirds of the total lending of UK banks to the domestic real economy, the
likelihood of a related banking stretch in the future is limited as the Annual Cyclical Scenario (ACS)
160
framework will help the FPC and the PRA Board in the setting of capital buffers to match the risk
environment and ensure resilience of the banking system.
In order to address these risks, the UK authorities have taken several measures, mainly targeting
the household stretch and the banking stretch. Some of these policies also target the collateral
stretch at the same time.
To increase resilience of the banking sector, stress tests with severe housing market downturns in
the adverse scenarios have been used since 2014 to determine the need for additional capital addons. The stress-test scenarios in 2016 are very severe – the RRE price falls are much bigger than
in the EBA 2016 stress test and in the United States Comprehensive Capital Analysis and Review.
In addition, the RRE price shock in the annual stress-test scenario will increase with the size of
imbalances in the housing market. This will guard against banking stretch in the future, by ensuring
that the amount of capital banks hold against mortgage lending rises if policymakers judge that
RRE prices are above equilibria, with elevated risks of a fall.
To target lending standards in the owner-occupier market, and thus the household stretch and to
some extent the collateral and banking stretch, new rules on lending standards have been set. Key
elements are a stricter affordability assessment for borrowers (including interest rate stress tests),
formalised requirements for income verification and the requirement for a credible repayment
strategy for borrowers receiving an interest-only loan. New interest-only loans have decreased
significantly from 34% (Q1 2008) to 1.6% (Q1 2016). In addition, following a review of outstanding
interest-only mortgages, the FCA has worked together with lenders to ensure that lenders contact
borrowers to prompt them to check that their plan for repaying their mortgage is on track and to
consider the options available to them – including switching to a repayment mortgage if it is
affordable for the borrower to do so. These policies have already reduced the stock of interest-only
loans from 31% to 23% between Q3 2013 and Q1 2016. This also decreases the LTV of the stock
as well as household indebtedness.
In the area of buy-to-let, the authorities are ensuring prudent lending standards by clarifying their
expectations regarding minimum lending standards for buy-to-let mortgage contracts. On 29
161
September the PRA published a Supervisory Statement on underwriting standards. This included
an affordability assessment, subject to minimum stressed interest rates (of a 2 p.p. rise in interest
rates or a minimum 5.5% stressed mortgage rate). Even before the referendum outcome, growth in
BTL mortgage lending was expected to slow as a result of recent tax changes (to stamp duty and a
reduction in mortgage interest tax relief) as well as the release of the PRA’s Supervisory Statement.
Moreover, an LTI flow limit was introduced in June 2014 to prevent the risk of an increase in the tail
of highly indebted households. Lenders should not extend more than 15% of their total number of
new residential mortgages at LTI ratios at or greater than 4.5. This measure was intended as an
insurance measure and was therefore not intended to be immediately binding in aggregate.
Although the current overall share of LTIs above 4.5 is significantly lower than 15%, this measure

160

For more information see:
http://www.bankofengland.co.uk/financialstability/Documents/stresstesting/2016/keyelements.pdf.

161

For more information see: http://www.bankofengland.co.uk/pra/Documents/publications/ss/2016/ss1316.pdf.

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seems to already have had a direct impact on individual lenders who took action to avoid breaching
the limit and an indirect impact on the market via market sentiment. The share of new mortgages
extended with high LTI ratios (i.e. with an LTI ratio of above 4.5) fell from 10.1% in Q2 2014 to 7.6%
in Q2 2015; however, it has since risen again to around 9% as at Q1 2016. As part of the same
package of measures, in June 2014 the FPC also recommended that, when assessing affordability,
mortgage lenders should apply an interest rate stress test that assesses whether borrowers could
still afford their mortgages if, at any point over the first five years of the loan, the Bank of England’s
monetary policy rate (Bank Rate) were to be 3 percentage points higher than the prevailing rate at
origination. The FPC reviews whether its macroprudential policy stance is appropriate on a regular
basis, and will do this again in the second half of 2016. If it feels an adjustment is required, it has
the tools to be able to change the LTI calibration, or adopt an LTV or DTI policy quickly and
effectively. The FPC also has good quality loan-level data allowing it to carry out thorough analysis
of the impact of its actions.

Situation after the UK’s referendum on EU membership in June 2016
It is early days yet, but there is growing evidence that the outlook for the UK housing market, which
showed tentative signs of weakening before the referendum, has weakened further since. The
growth rate of RRE prices, on a three month-on-three month annualised basis, slowed to 5% in
162
July, from a recent peak of 9% in February (last exceeded in September 2014). This slowing was
more marked in London, where prices were unchanged in Q2 2016 and growth was below the UK
average for the first time since 2013.
There is little hard data on the housing market since the referendum. But the evidence available
suggests that the outlook for property markets has significantly deteriorated. On a month-on-month
basis, RRE prices fell by 0.2% in July. In the immediate aftermath of the referendum, house
builders’ share prices dropped sharply (by 30% in the following week), and consumer confidence
fell by its sharpest monthly move for over two decades. A number of leading indicators also suggest
that the leave vote will put significant downward pressure on both activity and prices (e.g. the
surveys by RICS Residential Market Survey of Chartered Surveyors for the months of June and
163
July 2016, which are one of the best leading indicators of momentum in the housing market) .
In the August Inflation Report, the Bank of England’s MPC revised down its near-term outlook for
the UK economy and the housing market substantially. The MPC expected aggregate RRE prices
to decline a little over the next year, while the level of housing transactions is expected to remain
broadly flat. Staff projections consistent with the MPC’s forecast pointed to a slowdown in mortgage
lending growth, reflecting subdued demand. GDP was expected to grow by 2.0% in 2016 and fall to
0.8% in 2017 (the pre-referendum growth forecast for 2017 was 2.3%).
As a result of the revised macroeconomic outlook, some of the risks stemming from the household
and collateral stretches may start to materialise – this could amplify the impact of the shock from
the vote to leave the EU and increase the direct and indirect risks to financial stability. If prices fall
in the short-to-medium term due to higher uncertainty/lower confidence, this implies that the value
of banks’ collateral against their mortgage lending will fall and could also imply negative wealth
effects for households (however, the share of borrowers expected to fall into negative equity as a

162

Based on two RRE price indices monitored by the Bank of England (Halifax and Nationwide indices).

163

http://www.rics.org/Global/6._WEB_%20June_2016_RICS_UK_Residential_Market_Survey_ri.pdf.

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164

result is expected to be considerably lower than experienced in 2009). Some households might
find it more difficult to service their debts if unemployment rises and/or income growth falls, though
165
the recent decline in Bank Rate could mitigate this to some extent. And such households could
affect broader economic activity by cutting back sharply on expenditure in order to continue to
service their debts. If the number of borrowers defaulting on their mortgage rises, this could lead to
losses for banks, especially if accompanied by a fall in RRE prices. The growing and sizeable buy166
to-let sector in the UK has the potential to amplify a downturn in the housing market. Buy-to-let
investors are more likely to sell if RRE prices are expected to fall; however, the decline in Bank
167
Rate, which helps protect the cash flow of the investment, should mitigate this channel.
However, the Bank of England has taken action to ensure that the UK banking system is resilient to
a very large housing market shock. The Bank of England stress tests conducted in recent years
assessed the resilience of the banking system to much more severe scenarios than those that are
currently expected under the central projection by the Bank of England’s MPC in its August Inflation
Report. These stress tests ensured banks were capitalised not just to withstand the stress, but also
to maintain the supply of lending throughout. The 2014 stress test, for example, incorporated a 35%
fall in RRE prices and a near doubling in unemployment (to around 12%). This is considerably more
severe than the August Inflation Report projections, which incorporate a small fall in RRE prices
and a small increase in unemployment to around 5.6% in 2018. Given this, it seems that UK banks
would be resilient enough to withstand a housing market shock if household and collateral stretch
vulnerabilities were to crystallise in the near term.
However, it is important to note that there is considerable uncertainty about the impact of the vote
to leave the EU. It is impossible to foresee developments in property markets with any accuracy at
this juncture. Conversely, it is also possible that the slowdown in the housing market could prove to
be temporary and, after a pause, RRE prices, mortgage approvals and household debt could begin
to grow again. In this scenario, vulnerabilities related to residential real estate would continue to
rise. It is therefore important that the FPC monitors developments closely and adjusts
macroprudential policy accordingly.
Looking ahead, it will be necessary to ensure that any adjustment in the housing market proceeds
at an appropriate pace and that new imbalances do not emerge, against a backdrop of uncertainty
about the UK’s future ties with the EU.
In summary, given that the main risks relating to RRE in the UK have changed in response to
developments after the referendum and the high level of uncertainty about future developments, it
is very difficult to make an assessment of the medium-term vulnerabilities relating to RRE in the
UK, or of the impact of the policy measures taken to target them to date. It is not yet possible to
judge whether the vulnerabilities that had accumulated will now begin to crystallise or whether, in
time, they might instead continue to grow. The appropriate policy response is likely to differ
between these two scenarios. Nevertheless, in the light of Bank of England analysis, it seems that
the UK banking system would be resilient enough to withstand a housing market shock if household

164

In the August 2016 Inflation Report, the Bank of England showed that consumption growth has been closely related to RRE
price growth in the UK over the past 30 years (page 19, as above fn. 51).

165

As noted by the Bank of England in its July Financial Stability Report (page 12).

166

17% of the stock of total secured lending is accounted for by buy-to-let mortgages, and the gross flow of buy-to let lending
in 2015 was close to its pre-crisis peak (page 13, ibid.).

167

Interest rate expectations have declined following the MPC decision to lower interest rates in August 2016.

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and collateral stretch vulnerabilities were to crystallise given the steps taken by the UK authorities
to ensure that the banking system is capitalised against such adverse scenarios.

Table UK.1
Summary assessment – The United Kingdom
Summary RRE risk
assessment narrative

There is currently a high degree of uncertainty about the medium-term outlook for the UK housing market. From a
macroprudential perspective, there appear to be risks under different scenarios for the housing market – either
through the crystallisation of accumulated vulnerabilities, particularly related to household indebtedness and the
interaction with elevated RRE prices, or through the further build-up of vulnerabilities.
RRE vulnerabilities had built up before the referendum – they related to the interaction of a household stretch (due
to household indebtedness) and a collateral stretch (as indicated by RRE prices that were rising from already
elevated levels and decoupling from rent and income growth rates).
The UK residential real estate market is potentially at a turning point. Given the uncertainty of the implications of
the UK’s referendum on EU membership, it is not yet possible to judge whether the vulnerabilities that had
accumulated will now begin to crystallise or whether, in time, they might instead continue to grow.
The outlook for the UK economy and housing market has been revised down: the Bank of England expected in its
August Inflation Report aggregate RRE prices to decline a little over the next year, and the level of mortgage
approvals to be lower. If that forecast proves to be correct, it would slow the pace of build-up in mortgage debt and
therefore reduce vulnerabilities in the medium term. However, an economic slowdown could lead to the
crystallisation of some risks – for example, if unemployment rises and/or income growth falls, then some
households may find it more difficult to service their debts.
However, it is also possible that the slowdown in the housing market could prove to be temporary and, after a
pause, RRE prices, mortgage approvals and household debt could begin to grow again. In this scenario,
vulnerabilities related to residential real estate would continue to rise.

Policy assessment given
risks

Not directly assessed given the uncertain impact of the vote to leave the EU on the medium-term outlook
for the UK housing market
But it is considered that, although the build-up of risk through the household income and collateral stretch channels
appears to have abated, the probability of risks through these channels materialising has increased in the short-tomedium term, given the increased level of uncertainty and the lower economic growth projections.
Conversely, it is also possible that the slowdown in the housing market could prove to be temporary and, after a
pause, RRE prices, mortgage approvals and household debt could begin to grow again. In this scenario,
vulnerabilities related to residential real estate would continue to rise.
The appropriate policy response is likely to differ between these two scenarios.
Therefore, it will be important for the UK authorities to monitor developments closely and adjust macroprudential
policy in light of them. Looking ahead, it will be necessary to ensure that any adjustment in the housing market
proceeds at an appropriate pace and that new imbalances do not emerge.

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Table UK.2
Summary of risks and policy measures – The United Kingdom
Household stretch

Collateral stretch

Banking stretch

Summary risk assessment/main
risks

There is uncertainty about the
economic outlook for the UK
economy and housing market, but
the risk of vulnerabilities
crystallising in the household
stretch have increased. The ability
of some households to service their
debts could be materially affected
in the event of weaker employment
and income growth, though the
effect of this will be partially
mitigated by the recent cut in Bank
Rate. In addition to increased direct
credit risks to banks, this would
also magnify the initial economic
shock as households would need to
reduce their consumption in order
to continue servicing their mortgage
loans. Given the overall elevated
level of household indebtedness
(the DTI ratio was 130% in Q1
2016), the impact of an income or
interest rate shock to the UK
economy may be significant.
But if the slowdown in the housing
market proves to be temporary,
then household debt could continue
to rise in the medium term.

Risks related to collateral stretch
have been a growing vulnerability in
recent years. It is difficult to judge
whether prices are
over/undervalued as various
indicators send different signals.
However, price-to-rent and price-toincome ratios indicate that RRE
price growth has been decoupling
from rent growth and income
growth (although these measures
do not take into account structural
factors such as the fall in long-term
interest rates). In 2015, nominal
(but not real) RRE prices exceeded
their pre-crisis peak.
However, the vote to leave the EU
appears to have significantly
lowered the outlook for the housing
market – the Bank of England
expects prices to decline a little
over the coming year. This would
imply a fall in the value of banks’
mortgage collateral and would
lower household wealth, which
could affect consumption.
But if the slowdown in the housing
market proves to be temporary,
then house prices could continue to
rise in the medium term.

Direct credit risk is considered to be
limited. Second-round effects could
be regarded as the main risk, but
stress-test results indicate that the
banking system is resilient enough
to withstand severe shocks.
If the economic outlook deteriorates
following the vote to leave the EU,
the probability of default on
mortgages may rise. If
accompanied by a fall in some
property prices, this could lead to
significant losses for banks.

Summary of policy measures
(implemented, planned, under
consideration)

Implemented:
LTI flow limit of 4.5 for 85% of
owner-occupier mortgages (lenderby-lender basis)

Implemented:
FCA Mortgage Market Review,
including prescribed affordability
assessment and new standards
making it more difficult to qualify for
an interest-only (IO) mortgage
(introduced in April 2014)

Implemented:
Bank of England concurrent stresstesting framework: annual stress
tests of banks’ capital adequacy for
severe housing market shocks

FPC Recommendation on interest
rate stress tests to mortgage
lenders when assessing
affordability of borrowers
PRA measures on BTL
underwriting standards (September
[1]
2016)

FCA review of IO mortgages in the
stock of lending, and related followups with firms regarding their IO
borrowers (2013 onwards)
FPC’s Stress Testing Framework
(see also banking stretch)
PRA measures on BTL
underwriting standards (September
2016) [1]

Assessment of policy measures

Not directly assessed given the
uncertain impact of the vote to
leave the EU on the medium-term
outlook for the UK housing market.
But there is an increased risk that
vulnerabilities related to household
stretch begin to crystallise in the
short-to-medium term.

Not directly assessed given the
uncertain impact of the vote to
leave the EU on the medium-term
outlook for the UK housing market.
But there is an increased risk that
vulnerabilities related to collateral
stretch begin to crystallise in the
short-to-medium term.

Leverage ratio requirement for
major UK banks and building
societies
Currently out for consultation:
PRA measures on BTL
underwriting standards (see also
collateral stretch) [1]
Measures to reduce the
procyclicality of IRB risk weights

Not directly assessed given the
uncertain impact of the vote to
leave the EU on the medium-term
outlook for the UK housing market.
But there is an increased risk that
vulnerabilities relating to banking
stretch increase. Nevertheless, the
banking system seems to be
resilient against such scenarios.

[1] This is already the basis of discussions between PRA supervisors and mortgage lenders.

Household stretch
In the UK, the main risk connected to residential real estate is related to the household stretch. The
household stretch assessment is primarily based on the relatively high debt levels in the UK
household sector; however, it also takes into account the debt dynamics, distributional aspects and
interactions with other stretches, in particular the collateral stretch. However, the aggregate
household debt-to-income ratio fell between 2008 and 2012-13, and has remained flat since then.

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And, as discussed in Section 2.1.2, there is considerable uncertainty around the sustainable level
168
of household debt.
New borrowing at high loan-to-income ratios still remains significant (around 9% as at Q1 2016)
and the aggregate household debt-to-income ratio has stabilised at high levels (130% as at Q1
2016). Moreover, around half of mortgagors are on floating rate contracts, which make them
vulnerable to rises in interest rates, but can also be a mitigating factor when rates fall in periods of
stress. The stock of interest-only loans to owner-occupiers fell from 31% in Q3 2013 to 23% in Q1
2016 (this also has implications for the collateral stretch). Such factors create potential for indirect
risks to the economy and financial system from household indebtedness, e.g. if incomes fall or
interest rates rise without being accompanied by income growth. Micro data show evidence that
high levels of household debt have been associated with deeper downturns and more protracted
169
recoveries in the United Kingdom and internationally. However, the decrease in the share of
highly indebted households (i.e. with a debt-to-income ratio of above 5) indicates some decrease in
the risk of vulnerabilities that may arise due to income and interest rate shocks.
Most of the increase in net lending has been in the BTL market driven by structural factors and
strong competition. Mortgage lending to owner-occupiers has remained very subdued since the
financial crisis. Although the BTL market is more sensitive to interest rate shocks and the impact of
individual loans on lenders’ balance sheets is potentially larger given higher loss given default, the
risks from indebtedness stem largely from lending to owner-occupiers who cut back consumption
following a shock in order to meet mortgage payments. As BTL investors do not account for a
significant share of aggregate income and they can sell their properties if unable to repay their
loans, they present less of a risk via the indebtedness channel. However, BTL investors have the
potential to amplify housing cycles, as they are more likely to sell if RRE prices are expected to fall.
However, any decline in interest rates, which protects the cash flow of the investment, should
mitigate this channel. The stamp duty tax increase introduced in April 2016 (for BTL and second
homes), the mortgage interest tax relief caps to be introduced in 2017 and the PRA Supervisory
Statement were expected to slow growth in BTL mortgage lending, even prior to the outcome of the
EU referendum.
The UK authorities have taken several initiatives to influence lending standards and thus to reduce
the household stretch. Following an extensive review of lending standards (Mortgage Market
Review, MMR), the FCA introduced new rules for lending standards in April 2014. Key elements
are a stricter affordability assessment for borrowers, formalised requirements for income verification
and the requirement for a credible repayment strategy for borrowers receiving an interest-only loan.
New interest-only loans have decreased significantly from 34% (Q1 2008) to 1.6% (Q1 2016).
As a result of the 2013 review of interest-only mortgages, banks are now requested to encourage
existing customers with interest-only mortgages to switch to repayment mortgages. There is
evidence that this measure was successful, as the stock of interest-only loans fell by 34% between
end-2012 and Q1 2016, around two-thirds of which was due to redemption of interest-only loans
before their maturity date.

168

For example, the structural fall in interest rates in recent decades suggests that a higher debt level than previously may be
sustainable. And the sustainable level of indebtedness is also likely to vary between countries.

169

See Bank of England (2014) as above fn. 76.

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In June 2014 the FPC recommended the use of an interest rate stress test to assess whether
borrowers could still afford their mortgage if Bank Rate were 3 p.p. higher at any point over the first
five years of the loan. This is particularly important given the low level of interest rates and many
variable rate contracts. This policy locked in banks’ practices at the time. Since then, stressed
interest rates have remained at about 7% despite actual mortgage rates at origination continuing to
trend down.
A loan-to-income (LTI) flow limit became effective for loans extended from October 2014 to prevent
a further rise in the share of new lending at higher LTI multiples and high household indebtedness.
Mortgage lenders should not extend more than 15% of their total number of new residential
mortgages at LTI ratios of 4.5 or more. The limit is applied on a lender-by-lender threshold. It does
not cover buy-to-let and remortgages without increased principal. The share of new mortgages
extended with high LTI ratios fell back by 1 p.p. to 7.6% over the year to Q2 2015; however, it has
since risen again to around 9% as at Q1 2016. Although the current overall share of LTIs above 4.5
is significantly lower than 15%, this measure had a direct impact on individual lenders who took
action to avoid breaching the limit and an indirect impact on market sentiment. Since the policy was
introduced in 2014, the share of very high LTIs (i.e. more than 5) has decreased from 3% in Q2
2014 to 1% in Q1 2016.
The PRA has also looked more closely at BTL lending standards given the rapid growth in BTL
mortgage lending. A review revealed that some lenders apply somewhat looser standards. As a
consequence, the PRA issued supervisory guidance regarding minimum standards for BTL
mortgage contracts, also including affordability tests and interest rate stress tests. Even prior to the
outcome of the referendum, growth in BTL mortgage lending was expected to slow down, because
of upcoming tax changes (an increase in stamp duty and a reduction in mortgage interest tax relief)
as well as the release of the PRA’s Supervisory Statement.
Following the UK’s referendum on EU membership in June 2016, the outlook for the UK economy
has been revised down – thus, the build-up of risk through the household income and collateral
stretch channels may have abated, although the probability of risks through these channels
materialising may have increased. If they were to materialise, the associated negative household
income and wealth effects (e.g. if households need to reduce consumption in order to service their
mortgage loans) may reinforce the initial shock with negative direct and indirect effects on financial
stability. On 3 August the Bank of England’s Monetary Policy Committee introduced a package of
measures to support the economy (including an interest rate reduction and measures to ensure that
lower rates pass through to the real economy). These measures should also support mortgagors
and the housing market, and might lower the risk of crystallisation of household stretch
vulnerabilities.
Conversely, it is also possible that the slowdown in the housing market could prove to be temporary
and, after a pause, RRE prices, mortgage approvals and household debt could begin to grow
again. In this scenario, household stretch vulnerabilities would continue to rise in the medium term.

Collateral stretch
Risks related to collateral stretch have been a growing vulnerability in recent years: RRE prices
have been growing rapidly from already high levels and have been decoupling from rent and

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170

171

income growth rates. The recent IMF Article IV consultation discussed that RRE price growth
has been more than three times income growth recently and the price-to-rent ratio has risen steeply
since late 2012 (134% in Q1 2016).
The significant amount of collateralised RRE loans (approximately 69% relative to annual GDP)
indicates the negative effects that difficulties in RRE could have on financial stability and the real
economy. BTL lending has been the biggest contributor to net mortgage lending growth, but
172
accounts only for 17% of the flow of gross mortgage lending. This is partly due to owneroccupiers paying down and redeeming their mortgages, while BTL lending is mainly on interest173
only terms. While BTL investors rarely borrow at high LTVs , their mortgages tend to be extended
on interest-only terms meaning that the loan value can remain significant on lenders’ balance
sheets.
Mortgages in the UK generally have somewhat high loan-to-value ratios at origination relative to
other countries. The median LTV on the flow of new UK mortgage loans is around 75% at present,
a small drop from the 80% level before the financial crisis. However, the majority of loans amortise
over time and the share of mortgages with an LTV higher than 75% is only around 16% and the
share of mortgages with an LTV higher than 90% is only around 1.3% (Q1 2016). Furthermore,
despite the low risk weights (RWs) recorded for mortgages (i.e. average RWs of 11%), the FPC
has imposed a minimum leverage ratio on banks of 3%, which imposes an effective minimum
portfolio average risk weight of 35%. In addition, the FPC and PRA have capitalised banks against
very severe nominal RRE price falls through stress testing (i.e. the stress scenarios included a 35%
174
and 20% fall in RRE prices for 2014 and 2015, respectively).
Some of the above-mentioned policy measures also target collateral stretch. The reduction of new
and existing interest-only loans for owner-occupiers will reduce the LTV ratios in the portfolio and
decrease the loss given default, ceteris paribus. The new guidelines for BTL lending could have
similar effects – anchoring affordability will help anchor LTV ratios given that a rise in LTV ratios will
make loans less affordable. Given that RRE price downturns are an important feature of stress
tests used to determine capital adequacy, banks might have an incentive to reduce high LTV ratios
(for more details, see below under banking stretch), especially considering the very sharp falls in
RRE prices embedded in the stress scenarios.
It is difficult to judge whether prices are over/undervalued as there are differing signals from
different indicators. Models that take into account the current low level of interest rates, such as
those used by the Bank of England, suggest that there are no signs of fundamental overvaluation.
Nonetheless, standard valuation metrics, such as the price-to-rent and price-to-income ratios,
indicate that RRE price growth has been decoupling from rent growth and income growth, though
these measures do not take into account structural factors such as the fall in long-term interest
rates. In the UK, both price-to-income and price-to-rent indicators have been rising rapidly in recent
years relative to other EU countries (see Table C.1 in Annex C). And, on these metrics, London
prices look more stretched relative to other regions. The nominal RRE price level exceeded its pre-

170

Though these measures do not take into account structural factors such as the fall in long-term interest rates.

171

IMF (2016) as above fn. 159.

172

Buy-to-let amounts to around 17% of the stock of secured lending.

173

Only 10% of the BTL is at an LTV>75%, and only 3% is at an LTV>80%.

174

Stress testing the UK banking system: 2015 results, Bank of England, December 2015.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
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136

crisis peak in 2015, although, of course, this is in the context of much lower long-term interest rates
(in real terms, RRE prices remain below pre-crisis peaks).
According to an average of lenders measure, RRE price growth slowed on a three month-on-three
month annualised basis to 4.4% in June, from a peak of 8.8% in February. If there are concerns
that prices are overvalued, or if RRE price increases continue, any future price correction will have
a negative impact on the housing collateral value. RRE price rises have been driven by the slow
response of supply (e.g. as a result of restrictive planning regulations) to the higher level of
demand. Further RRE price rises may be expected in the medium term if these supply and demand
imbalances continue. However, the weaker outlook for the housing market following the UK’s
referendum on EU membership may suggest a period of slower growth and potentially even falling
prices in (some parts of) the UK. However, due to the unusual nature of the shock, there is a high
degree of uncertainty about future RRE price developments at present.

Banking stretch
Given the potential for collateral stretch vulnerabilities and the fact that mortgages account for
approximately two-thirds of UK banks’ total lending to the real economy, there may be a related
banking stretch in the future. Nevertheless, the annual stress-test programme should ensure that
the UK banking system is well capitalised against adverse scenarios, including scenarios of
significant RRE price falls. These stress tests ensured banks were capitalised not just to withstand
the stress, but also to maintain the supply of lending throughout. The RRE price shock in the
annual stress-test scenario will increase with the size of imbalances in the housing market. This will
guard against banking stretch in the future, by ensuring that the amount of capital banks hold
against mortgage lending rises if policymakers judge that RRE prices are above equilibria, with
elevated risks of a fall.
Nevertheless, the economic outlook has deteriorated since the referendum. As a result, the
probability of default on mortgages may rise somewhat (as some households may find it more
challenging to service their debt if unemployment rises or income growth falls, etc.). If accompanied
by a fall in some property prices, this could lead to losses for banks.
Analysis by the Bank of England suggests that any potential deterioration in unemployment as a
result of the referendum decision, and any fall in the level of RRE prices, will be much less severe
than the types of scenarios under which UK banks have been stress-tested in recent years. Results
of the stress test were taken into account in the evaluation of capital adequacy of individual banks
and led to higher capital requirements for banks with higher vulnerabilities. These stress tests
ensured banks were capitalised not just to withstand the stress, but also to maintain the supply of
lending throughout. The 2014 stress test, for example, incorporated a 35% fall in RRE prices and a
near doubling in unemployment (to around 12%). This compares with a small fall in RRE prices in
the MPC’s central forecast and a small increase in unemployment to around 5.6% in 2018. The
2016 stress test will again contain a severe adverse scenario for residential and commercial real
estate. Given this, it seems that UK banks would be resilient enough to withstand a housing market
shock if household and collateral stretch vulnerabilities were to crystallise in the near term.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Analysing vulnerabilities in residential real estate39F

137

Table UK.3
Additional information on instruments and data available to micro and macro supervisory
authorities – The United Kingdom
Do the macro and micro supervisory
authorities have the powers necessary to
implement/amend policy quickly and
effectively if/when required?

The FPC regularly monitors risks to financial stability stemming from the housing market; has
a range of tools at its disposal to take action to mitigate those risks, rapidly and within a clear
framework; and has adequate data to assess risks and calibrate its tools.
The FPC was granted powers of Direction by the Government over loan-to-value and debt-toincome limits for lending to owner-occupiers of residential property in February 2015 and the
Treasury has consulted on giving powers of direction to the FPC on buy-to-let mortgage
lending and will respond to that consultation in the coming months.
The FPC has the power to make recommendations to the regulators – the PRA and the FCA
– about the exercise of their functions, such as to adjust the rules facing banks and other
regulated financial institutions. The FPC is also able to make recommendations to HM
Treasury, including on additional macroprudential tools that the Committee considers that it
may need, and on the “regulatory perimeter” – that is, both the boundary between regulated
and non-regulated activities within the UK financial system, and the boundaries of different
regulators within the regulated sector. The FPC also has a broader power to make
recommendations to any other persons. For example, this power allows the FPC to make
recommendations directly to the industry or to independent bodies such as the Financial
Reporting Council.
The FPC and the PRA Board design stress tests annually and use those to inform the setting
of capital buffers for participating firms. The PRA has the power to set firm-specific capital
buffers (the PRA buffer) and the FPC has the ability to set system-wide capital buffers via the
countercyclical capital buffer and a power of direction over sectoral capital requirements,
which enables the FPC to change capital requirements on exposures of banks to specific
sectors that are judged to pose a risk to the stability of the financial system as a whole.
The FPC also has powers of Direction over leverage ratio requirements and buffers for banks,
building societies and PRA-regulated firms.

Do the macro and micro supervisory
There do not seem to be data issues that would hamper the implementation of certain
authorities have the necessary data to monitor policies. The UK authorities are collecting a wide range of data, including, amongst others,
the risks and the impact of policy measures?
loan-level data on the flow of new mortgage lending as well as core financial and economic
indicators, which they are periodically reviewing in conjunction with analysis of the drivers of
movements.

Annex with charts
Chart UK.1
Household debt-to-income ratio

Chart UK.2
Loan-to-income multiples for
new mortgages

(percentage)

(percentage of new mortgages)
LTI ≥ 4.5
LTI ≥ 5
12

160
140

10
120
8

100
80

6

60
4
40
2

20
0
1988

1992

1996

2000

2004

2008

2012

2016

Sources: Office for National Statistics and Bank of England calculations.
Notes: Gross debt as a percentage of a four-quarter moving sum of
disposable income. Includes all liabilities of the household sector except
for the unfunded pension liabilities and financial derivatives of the nonprofit sector. The household disposable income series is adjusted for
financial intermediation services indirectly measured (FISIM).

0
2005

2006

2008

2009

2010

2012

2013

2014

2016

Sources: FCA Product Sales Database and Bank of England
calculations.
Notes: FCA Product Sales Database includes regulated mortgage
contracts only. LTI ratio calculated as loan value divided by the total
reported gross income for all named borrowers. Chart excludes lifetime
mortgages, advances for business purposes and remortgages with no
change in the amount borrowed.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Analysing vulnerabilities in residential real estate39F

138

Chart UK.4
UK house prices

Chart UK.3
Distribution of household
debt-to-income ratios
(x-axis: total household debt-to-income ratio; y-axis: percentage of
households)
2011
2012
2013

(percentage)
growth - 3M-on-3M annualised (right axis)
level -Oct 2007=100 (left axis)
growth - YoY (right axis)

2014
2015

20

120

50

15

45
100
40

10

35

80

5

30

0
60

25

-5

20

40

-10

15
-15
10

20
-20

5
0
2005

0
<1

1-3

3-5

5+

Sources: NMG Consulting survey and Bank of England calculations.

-25
2007

2009

2011

2013

2015

Sources: Halifax/Markit, Nationwide and Bank of England calculations.
Notes: House prices are an average of the Halifax and Nationwide
measures. Nationwide house price data have been seasonally adjusted
by Bank of England staff.

Chart UK.5
Major lenders’ mortgage books by indexed LTV
0% < LTV <= 50%
50% < LTV <= 75%
75% < LTV <= 90%

90% < LTV <= 95%
95% < LTV <= 100%
100% < LTV

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
2009

2010

2011

2012

2013

2014

2015

Source: Bank of England regulatory data.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
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139

Chart UK.6
Share of mortgages on fixed rates
(percentage on a fixed rate)
flow of new mortgages
stock of exsisting mortgages
100
90
80
70
60
50
40
30
20
10
0
2004

2006

2008

2010

2012

2014

2016

Source: Bank of England.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
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140

Conclusions
The analysis in this report forms the basis for the warnings issued by the ESRB on mediumterm vulnerabilities in the residential real estate sectors of eight EU Member States. On
22 September, the ESRB General Board adopted warnings to eight Member States about medium175
term vulnerabilities in their residential real estate sectors. The macroprudential rationale for why
developments in the RRE sector can have significant implications for financial stability and the real
economy and the country-specific analysis behind these warnings are presented in this report.
Some EU Member States have been identified as having certain medium-term vulnerabilities
related to RRE that are a source of systemic risk to financial stability. An EU-wide quantitative
analysis identified those countries with vulnerabilities that have the potential to become material
risks in the medium term. This set of focus countries was then subject to country-specific analysis,
which took into account the wider institutional and structural context and relevant policy measures.
Based on this analysis, the ESRB concluded that medium-term vulnerabilities relating to residential
real estate which are a source of systemic risk to financial stability prevail in Austria, Belgium,
Denmark, Finland, Luxembourg, the Netherlands, Sweden and the United Kingdom; the ESRB
subsequently issued warnings to these Member States. In Estonia, Malta and Slovakia, the ESRB
considers that there are vulnerabilities in residential real estate, but that they are mitigated by
institutional factors or current prudential policies, which are expected to be sufficient in addressing
them.
Work is under way to fill data gaps and improve data quality to facilitate more informed
assessments of RRE-related vulnerabilities, as well as to develop the methodology for
country-based assessments of real estate vulnerabilities and the effectiveness of the related
prudential policies. The ESRB is aware of the shortcomings of many of the indicators used to
assess vulnerabilities in RRE. To address these shortcomings, a dedicated expert group was
established by the ESRB to seek to harmonise, improve and collect key indicators fit for crosscountry comparisons. Based on analysis by the expert group, on 31 October 2016 the ESRB
adopted a Recommendation on closing real estate data gaps (Recommendation ESRB/2016/14).
With this recommendation, which covers both the residential and commercial real estate sectors,
the ESRB aims to establish a more harmonised framework for monitoring developments in real
estate markets in the EU. The recommendation provides a common set of indicators that national
macroprudential authorities are recommended to monitor in assessing risks originating from the
176
real estate sector along with working definitions of these indicators. Such improvements in data
quality and access are vital given the importance of RRE for financial stability and macroprudential
policy. In addition, given the methodological challenges encountered during this work, in the
medium term the ESRB aims to develop a more quantitative framework for country-based
assessments of real estate vulnerabilities and the effectiveness of the related prudential policies.

175

The eight warnings are numbered as follows: ESRB/2016/05 (Austria); ESRB/2016/06 (Belgium); ESRB/2016/07
(Denmark); ESRB/2016/08 (Finland); ESRB/2016/09 (Luxembourg); ESRB/2016/10 (the Netherlands); ESRB/2016/11
(Sweden); and ESRB/2016/12 (the United Kingdom).

176

The ESRB monitors compliance with its recommendations via an "act or explain" mechanism. The deadline for
implementing the recommendation on closing real estate data gaps is end-2020.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Conclusions

141

Further efforts are needed to ensure that macroprudential authorities have suitable
macroprudential instruments at their disposal in order to effectively address vulnerabilities
arising from RRE. A wide range of measures have been used by Member States in order to
address the household, collateral and banking stretches. Commonly used macroprudential
measures include LTV limits, guidelines and recommendations to tighten lending standards, and
risk-weight adjustments. Beyond macroprudential instruments, policies that influence the incentives
of RRE investors or borrowers, such as changes to tighten the tax treatment of property or RRE
loans or amortisation requirements, have also been applied in several countries. However, there
are also examples of national authorities being constrained in their ability to target RRE risks
directly due to a lack of appropriate instruments within their control. This is particularly the case for
borrower-based measures that are not currently included in the EU legislation, such as LTI, DTI or
LTV limits. As these instruments have often proven to be efficient in addressing systemic risks, they
should be available to macroprudential policymakers in all EU Member States. However, the ESRB
is also of the view that such instruments – including decisions concerning their design,
implementation and application – should be in the hands of national macroprudential authorities.
Going forward, the ESRB will continue exercising its mandate for macroprudential oversight
of the EU financial system, including identifying risks related to RRE in the EU. The ESRB
will continue to monitor risks related to residential real estate in the EU, and where needed, issue
warnings and recommendations.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Conclusions

142

List of tables and charts 177
Table E.1

Summary assessments: focus countries

Chart 1.1

Importance of RRE for households, banks and the real economy

Table 1.1

Overview: repercussions from RRE-related crises

Chart 1.2

Housing busts and recessions: the role of credit

Chart 1.3

Interactions between house prices and household indebtedness

Table 2.1

Vulnerabilities in RRE across the EU: results from the indicator-based horizontal
assessment

Chart 2.1

Developments in collateral and household stretch

Table 2.2

Economic outlook in EU countries

Table 2.3

Banking stretch related to residential real estate: key indicators

Table 2.4

Structural and institutional features in RRE markets in selected countries

Table 2.5

Macroprudential policy measures, by the type of RRE risks they may directly
address

Chart 2.2

IMF event study estimates of the impact of macroprudential tools on mortgage
credit and house prices

Table AT.1

Summary assessment – Austria

Table AT.2

Summary of risks and policy measures – Austria

Table AT.3

Additional information on instruments and data available to micro and macro
supervisory authorities – Austria

Table BE.1

Summary assessment – Belgium

Table BE.2

Summary of risks and policy measures – Belgium

Table BE.3

Additional information on instruments and data available to micro and macro
supervisory authorities – Belgium

Table DK.1

Summary assessment – Denmark

Table DK.2

Summary of risks and policy measures – Denmark

Table DK.3

Additional information on instruments and data available to micro and macro
supervisory authorities – Denmark

Table EE.1

Summary assessment – Estonia

177

List does not include those charts presented alongside the country-specific analysis in Section 2.2.2 of the report.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
List of tables and charts176F

143

Table EE.2

Summary of risks and policy measures – Estonia

Table EE.3

Additional information on instruments and data available to micro and macro
supervisory authorities – Estonia

Table FI.1

Summary assessment – Finland

Table FI.2

Summary of risks and policy measures – Finland

Table FI.3

Additional information on instruments and data available to micro and macro
supervisory authorities – Finland

Table LU.1

Summary assessment – Luxembourg

Table LU.2

Summary of risks and policy measures – Luxembourg

Table LU.3

Additional information on instruments and data available to micro and macro
supervisory authorities – Luxembourg

Table MT.1

Summary assessment – Malta

Table MT.2

Summary of risks and policy measures – Malta

Table MT.3

Additional information on instruments and data available to micro and macro
supervisory authorities – Malta

Table NL.1

Summary assessment – The Netherlands

Table NL.2

Summary of risks and policy measures – The Netherlands

Table NL.3

Additional information on instruments and data available to micro and macro
supervisory authorities – The Netherlands

Table SK.1

Summary assessment – Slovakia

Table SK.2

Summary of risks and policy measures – Slovakia

Table SK.3

Additional information on instruments and data available to micro and macro
supervisory authorities – Slovakia

Table SE.1

Summary assessment – Sweden

Table SE.2

Summary of risks and policy measures – Sweden

Table SE.3

Additional information on instruments and data available to micro and macro
supervisory authorities – Sweden

Table UK.1

Summary assessment – The United Kingdom

Table UK.2

Summary of risks and policy measures – The United Kingdom

Table UK.3

Additional information on instruments and data available to micro and macro
supervisory authorities – The United Kingdom

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
List of tables and charts176F

144

Abbreviations
ASC

(ESRB)
Advisory
Scientific
Committee

DSR

debt service ratio

FPC

ATC

(ESRB)
Advisory
Technical
Committee

DSTI

debt service-toincome
(ratio/limit/cap)

FSA

BCBS

Basel
Committee on
Banking
Supervision

DTI

debt-to-income
(ratio/limit/cap),
debt-to-disposable
income
(ratio/limit/cap)

FSC

BIS

Bank for
International
Settlements

EBA

European Banking
Authority

BRRD

Bank Recovery
and Resolution
Directive

EC

BSI

balance sheet
items

Financial
Policy
Committee
(UK)
Financial
Supervision
Authority,
Financial
Supervisory
Authority

MIR

MFI interest
rates

MUFA

Monetary Union
Financial
Accounts

Financial
Stability
Committee

NBB/BNB

Nationale Bank
van
België/Banque
Nationale de
Belgique

FSR

Financial
Stability
Report

NBS

National Bank of
Slovakia

European
Commission

FX

foreign
exchange

NFA

National
Financial
Accounts

ECB

European Central
Bank

GDP

gross
domestic
product

NPL

non-performing
loan

HH

household

OECD

Organisation for
Economic Cooperation and
Development

BTL

buy-to-let

ECON

Committee on
Economic and
Monetary Affairs of
the European
Parliament

CBD

consolidated
banking data

EEA

European
Economic Area

I/O

interest-only
(loan)

OeNB

Oesterreichische
Nationalbank

CESEE

Central, eastern
and southeastern Europe

EIOPA

European
Insurance and
Occupational
Pensions Authority

IAS

International
Accounting
Standards

O-SII

other
systemically
important
institution

CCoB

capital
conservation
buffer

EMIR

European Market
Infrastructure
Regulation

IFRS

International
Financial
Reporting
Standards

p.p.

percentage
point(s)

CCP

central
counterparty

EMU

Economic and
Monetary Union

ILTV

indexed LTV

PRA

Prudential
Regulation
Authority (UK)

CCyB

countercyclical
capital buffer

ESA
2010

European System
of Accounts 2010

IMF

International
Monetary
Fund

PTI

price-to-income
(ratio/index)

CDS

credit default
swap

ESCB

European System
of Central Banks

IRB

internal
ratings-based
(approach)

PTR

price-to-rent
(ratio/index)

CET1

Common Equity
Tier 1

ESRB

European Systemic
Risk Board

LCR

liquidity
coverage ratio

RRE

residential real
estate

EU

European Union

LGD

loss given
default

RW

risk weight

SA

standardised
approach

CRD

CRD IV

CRR

CSSF

DNB

DG/MF

Capital
Requirements
Directive
Capital
Requirements
Directive IV
Capital
Requirements
Regulation
Commission de
Surveillance du
Secteur
Financier
(Luxembourg)
De
Nederlandsche
Bank
(ECB)
Directorate
General
Macroprudential
Policy and
Financial
Stability

FCA

Financial Conduct
Authority (UK)

LTI

loan-toincome
(ratio/limit/cap)

FI

Finansinspektionen
(Swedish FSA)

LTV

loan-to-value
(ratio/limit/cap)

SDW

(ECB) Statistical
Data Warehouse

FINFSA

Finanssivalvonta
(Finnish FSA)

MCI

mortgage
credit
institution

SMEs

small and
medium-sized
enterprises

FMA

Finanzmarktaufsicht
(Austria)

MFI

monetary
financial
institution

SRB

systemic risk
buffer

FMSB

Financial Market
Stability Board
(Austria)

MID

mortgage
interest
deductibility

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Abbreviations

145

Country abbreviations
AT

Austria

AU

Australia

BE

Belgium

BG

Bulgaria

CA

Canada

CH

Schwitzerland

CY

Cyprus

CZ

Czech Republic

DE

Germany

DK

Denmark

EE

Estonia

ES

Spain

FI

Finland

FR

France

GR

Greece

HR

Croatia

HU

Hungary

IE

Ireland

IT

Italy

JP

Japan

KR

South Korea

LT

Lithuania

LU

Luxembourg

LV

Latvia

MT

Malta

MX

Mexico

NL

Netherlands

NO

Norway

PL

Poland

PT

Portugal

RO

Romania

SE

Sweden

SI

Slovenia

SK

Slovakia

UK

United Kingdom

US

United States

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
Abbreviations

146

List of contributors 178
Banca d’Italia

Mr Francesco Zollino *

Banco de España

Mr Christian E. Castro **

Sveriges Riksbank

Mr Robert Emanuelsson **

ESRB Secretariat

Mr Tuomas Peltonen ***

* Leader of the Methodology Team
** Leaders of the Country Teams
*** Coordinator
Bank of England

Ms Tracy Wheeler

Banque centrale du Luxembourg

Mr Gabriele Di Filippo

Banque de France

Mr Antoine Lalliard

Bulgarian National Bank (Българска народна банка)

Mr Mihail Mihaylov

Bulgarian National Bank (Българска народна банка)

Ms Silvia Prokopieva

Central Bank of Cyprus (Κεντρική Τράπεζα της Κύπρου)

Ms Elena Mousarri

Central Bank of Malta

Ms Alexia Pisani

Central Bank of Malta

Ms Wendy Zammit

Česká národní banka

Ms Hana Hejlova

Commission de Surveillance du Secteur Financier

Mr Bob Muller

Danmarks Nationalbank

Mr Malte Lisberg Jensen

Danmarks Nationalbank

Mr Morten Hedegaard Rasmussen

Danmarks Nationalbank

Mr Oliver Juhler Grinderslev

De Nederlandsche Bank

Mr Remco Molen

Deutsche Bundesbank

Mr Michael Richter

Deutsche Bundesbank

Ms Nataliya Barasinska

ECB

Ms Marianna Caccavaio

ECB

Ms Federica Ciocchetta

ECB

Mr Benjamin Klaus

ECB

Ms Anne Koban

ECB

Mr Marco Lo Duca

ECB

Mr Giulio Nicoletti

Eesti Pank

Mr Hanno Kase

ESRB Secretariat

Mr Sampo Tapio Alhonsuo

ESRB Secretariat

Ms Marisa Basten

ESRB Secretariat

Mr Elias Bengtsson

ESRB Secretariat

Mr Morten Niels Haastrup

ESRB Secretariat

Mr Etienne Lepers

ESRB Secretariat

Ms Katie Rismanchi

178

The ESRB would in particular like to thank the colleagues of the ECB - Federica Ciocchetta, Marco Lo Duca, Benjamin
Klaus and Giulio Nicoletti - for their work on the horizontal analysis (Section 2.1). Special thanks goes to the team leaders,
Christian E. Castro, Robert Emanuelsson and Francesco Zollino, and their respective teams for their hard work. Finally, we
would like to thank the country contact persons for providing information, comments and fact checking.

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
List of contributors177F

147

ESRB Secretariat

Mr Virgilijus Rutkauskas

Financial Supervision Commission

Ms Kalina Hadjinedelcheva

Financial Supervision Commission

Ms Sashka Asparouhova

Finansinspektionen

Mr Johan Berg

Finansinspektionen

Mr Roland Nilsson

Finanssivalvonta (FIN-FSA)

Mr Peik Granlund

Finanstilsynet

Mr Theis Jørgensen

Finanzmarktaufsicht (FMA)

Mr Timo Broszeit

HANFA

Mr Mario Radaković

Hrvatska Narodna Banka

Ms Dragica Sitar

Hrvatska Narodna Banka

Ms Ivana Herceg

Lietuvos Bankas

Mr Vaidotas Šumskis

Magyar Nemzeti Bank

Mr Sándor Winkler

Národná banka Slovenska

Mr Pavol Latta

Narodowy Bank Polski

Ms Joanna Waszczuk

Nationale Bank van België/Banque Nationale de Belgique

Mr Thomas Schepens

Nationale Bank van België/Banque Nationale de Belgique

Ms Mara Pirovano

Norges Bank

Mr Sverre Mehlum

Oesterreichische Nationalbank

Mr Gernot Ebner

Suomen Pankki – Finlands Bank

Ms Hanna Putkuri

ESRB
Vulnerabilities in the EU residential real estate sector November 2016
List of contributors177F

148

Annexes

ESRB
Annexes
List of contributors177F

149

Contents

Annex A – Overview of process and mandates

171

Annex B – Methodology – Horizontal method

173

Annex C – Additional key indicators for focus countries

178

Annex D – Overview of assessments by third parties

181

E SRB
Vulnerabilities in the EU residential real estate sector / November 2016
Contents
List of contributors177F

Annex A
Overview of process and mandates

Team-based organisational framework
In order to ensure a fair and independent treatment of each country taking into account all relevant
factors, a team-based organisational framework was developed. In total, there were five teams
(shown in Table A.1) comprising representatives of Member States and the ESRB Secretariat
which prepared the analysis. The final assessments of the focus countries were prepared by the
Country Teams and the ESRB Secretariat, which were supported by the RRE Methodology Team,
the ESRB Assessment Team on Macroprudential Measures and representatives of the focus
countries. The mandate and tasks of the different groups are shown in Table A.1 and the list of
participants is shown in the report.
In order to ensure consistency in the assessments, the Methodology Team developed a
methodology to judge the appropriateness and sufficiency of policy measures given residential real
estate (RRE) risks. However, the intention was not to ensure complete equivalence in the final
assessments; each country was assessed individually, since all have a unique institutional,
macroeconomic and policy environment. While a qualitative framework was used to supplement the
quantitative approaches in the horizontal analysis (described in more detail in Annex B) and for the
detailed country analysis (“vertical analysis”), data were still central to the analysis of the Country
Teams. Expert judgement and interactions with country representatives were used to interpret
metrics for each country. Annex C shows the values for different countries of key indicators that
are mentioned in the report.

ESRB
Vulnerabilities in the EU residential real estate sector / November 2016
Annex A
Overview of process and mandates

151

Table A.1
Mandates for the different teams of the ESRB Task Force for RRE
RRE Task Force: core
participant groups
Country Teams
(A and B)

Main tasks

Additional information

The Country Teams made their assessment from an RRE risk perspective. For each
of the vulnerabilities identified, the Country Teams assessed whether these could
pose a significant risk to financial stability. They took account of the relevant policy
measures in the country that could mitigate identified risks.

The Country Teams
interacted mainly via emails
and telephone calls. A faceto-face meeting was held in
April 2016 to discuss topics
with country representatives.

The focus countries were divided between Country Teams to reduce the burden on
the team members. Each Country Team had a chair; the two chairs sought to
maintain the consistency of approaches across countries.
A broad set of policies were taken into account, including prudential policies and
fiscal or structural measures. Measures were taken into account if they had already
been implemented or if it was confirmed that it had been decided to implement
them.
Methodology Team

Assess the analytical framework used by the ESRB Secretariat and the ECB for the
horizontal analysis of the vulnerabilities and provide concrete proposals on how to
improve it.
Assess the templates that were used by the Country Teams and provide concrete
proposals on how to improve them.
Propose criteria to the ESRB Assessment Team to enable it to make qualitative
judgements on the effectiveness of policies (macroprudential, microprudential and
other economic policies) addressing risks from residential real estate.

ESRB Assessment
Team on
Macroprudential
Measures

It was assessed whether the prudential policies that a country has implemented are
appropriate and sufficient to address the risks identified in that country.
The Assessment Team took account of policies of a macroprudential or
microprudential nature related to residential real estate that have been implemented
or are being planned by the responsible national authority/authorities. Other policies
(e.g. fiscal or structural policies) were noted as mitigating or amplifying factors.

The Methodology Team
interacted through several
teleconference meetings and
a face-to-face meeting in
Frankfurt.
A workshop to further develop
the analytical framework for
future use took place in July
2016.
The assessment was guided
by the framework provided by
the Methodology Team.
Individual teleconference
meetings were organised to
discuss each of the eleven
focus countries.

The Assessment Team provided input to the Country Teams relating to policy
assessments.
Representatives from
national authorities in
the focus countries
(“Country
representatives”)

Submitted self-assessments to the ESRB Secretariat and Country Teams, providing
details on their own assessment of RRE-related vulnerabilities and policies in their
respective countries.
Interacted with the Country Teams and the ESRB Secretariat in order ensure
maximum agreement, clarify data issues, provide information, etc.

The country representatives
participated in the
teleconference meetings of
the ESRB Assessment Team
on Macroprudential Measures
and also attended the face-toface meeting in April 2016 to
discuss topics with the
Country Teams.
They interacted with the other
teams and the ESRB
Secretariat on multiple
occasions at ESRB meetings
and via emails and telephone
calls.

ESRB
Vulnerabilities in the EU residential real estate sector / November 2016
Annex A
Overview of process and mandates

152

Annex B
Methodology – Horizontal method
The current RRE risk assessment framework has been developed jointly with the ECB (Directorate
General Macroprudential Policy and Financial Stability, DG/MF) in order to reach convergence of
risk identification and assessment methodologies between the ECB and the ESRB. The framework
builds on earlier ECB (DG/MF) and ESRB approaches to RRE analysis.
The RRE risk assessment framework consists of three steps: (1) preliminary screening of
vulnerabilities in RRE markets (RRE prices, lending conditions, household balance sheets)
focusing on the detection of “exuberant” developments; (2) analysis of the strength of the
expansion in RRE markets; and (3) assessment of banking sector resilience and potential
aggravating/mitigating institutional and structural factors.
In the first step, vulnerable RRE markets were identified on the basis of indicators covering
RRE prices, lending conditions and household balance sheets. The indicators used in this first
step are summarised in a scoreboard table, which consists of a heat map with relevant risk
thresholds and summary indicators to facilitate country rankings (Table 2.1 in the report). The
indicators in the scoreboard capture three risk categories and are explained in detail in Table B.1.
Specifically, the categories are:
•

RRE pricing: indicators capture potentially “exuberant developments in RRE markets”, which
relate also to stretched collateral values (and can feed into lending conditions);

•

lending conditions: indicators capture potentially “exuberant developments in lending
conditions”, which can relate to underpricing of risk and might also feed into RRE price
developments;

•

household balance sheets: indicators capture household vulnerabilities, which relate to
potential credit risk and its dynamics.

The scoreboard thresholds are guided by model evidence where possible and by the distribution of
the indicators, and the plausibility is checked on the basis of expert judgement. The dates of the
observations underlying the scoreboard are reported in Table B.2.
Two composite indicators, summarising the level of vulnerabilities in one country, are used to
facilitate an initial country ranking.
•

The average rating across indicators (penultimate column of the scoreboard) is an equally
weighted average of a discrete transformation of the individual indicators. Each indicator is
assigned a rating from 0 to 3 on the basis of the threshold it breaches (0 = no threshold
breached, 3 = highest threshold breached, indicating high risk). The summary indicator is
simply the average of the ratings of individual indicators. The first threshold of the composite
indicator is set at 1 (i.e. individual indicators breaching the first risk threshold on average) and
nd
rd
corresponds to a yellow colouring. The 2 (orange colour) and 3 (red colour) thresholds are
th
th
set on the basis of the 80 percentile and the 90 percentile of the distribution of the indicator
across countries and over time.

•

The composite indicator (last column of the scoreboard) reports the average distance (in
terms of standard deviation) of indicators from the lowest thresholds. It is calculated as an
equally weighted average of the standardised indicators. Standardisation is achieved by
deducting the lowest threshold from each indicator and dividing by the standard deviation of
the indicator (calculated across countries and over time). The first threshold of the composite

ESRB
Vulnerabilities in the EU residential real estate sector / November 2016
Annex B
Methodology – Horizontal method

153

indicator is set at 0 (i.e. individual indicators breaching the first risk threshold on average) and
nd
rd
corresponds to a yellow colouring. The 2 (orange colour) and 3 (red colour) thresholds are
th
th
set on the basis of the 80 percentile and the 90 percentile of the distribution of the indicator
across countries and over time.
As the resulting ranking of countries according to summary indicators critically depends on the
thresholds, the set of indicators used and the weighting scheme used for the aggregation, a
number of robustness checks are performed. Specifically, the robustness of the initial country
rankings is assessed by: (i) using a composite indicator that does not rely on thresholds (see
Table B.3); and (ii) looking at the ranking of countries stemming from a simulation where the
average rating indicator is calculated by using 10,000 sets of random weights (see Chart B.1). The
latter exercise ensures that the ranking is robust to the weighting scheme and does not over-rely on
a specific indicator. Finally, in order to ensure that the ranking is not excessively affected by the
benchmark thresholds, which in some cases are solely based on judgement, the simulation is
repeated in four different settings by moving all the thresholds up by 5% and 10% and down by 5%
and 10%.

Chart B.1
Robustness check: simulation using random weights
ranking based on simulation, (right-hand side)
average rating across indicators, (left-hand side)
3

120
96

100
86

2

80
61
51

49

60
47
34

1

40

32
16

20

12
6

3

2

1

1

1

1

1

0

0

0

0

0

0

0

0

0

0

LV PT

SI

0

0
SE LU MT UK DK BE

FI

AT SK CY NL GR FR RO LT PL DE IE CZ BG EE ES HR HU IT

The second step of the assessment consists in determining the position of a country in the
housing cycle in relation to the household and the collateral stretches by looking at indicators
capturing the “strength” of the expansion. This is important in order to incorporate cyclical
considerations in the policy assessment and, therefore, decide on the appropriate set of policy
instruments to address risks. The analysis on the household and collateral stretches is
complemented by an assessment of risks coming from the banking sector stretch
(exposures of the banking system to risks and consequent assessment of resilience).
In a third step, the vulnerable RRE markets are assessed on the basis of institutional and
structural factors that might act as amplification or mitigation mechanisms for shocks, as
detailed in the relevant section of the report.

ESRB
Vulnerabilities in the EU residential real estate sector / November 2016
Annex B
Methodology – Horizontal method

154

Table B.1
Definitions and sources for horizontal risk assessment indicators
Indicator

Description

Data sources
Collateral stretch

RRE price growth

RRE price index (2007 = 100), 12-month growth, %
The indicator measures dynamics of real estate prices with the goal of
detecting exuberant price developments. The lower threshold for the
indicator is set close to an early warning model threshold with balanced
preferences between type I and type II errors.

Macroprudential database (ECB
SDW)

RRE price relative to peak
prior to 2014

Ratio of current house prices to peak level of house prices before 2014
The indicator is a coarse measure of RRE price overvaluation. The first
threshold is arbitrarily set to 0.9 to flag when the RRE price index is close to
the historical record.

Macroprudential database (ECB
SDW)

RRE valuation measure,
house price-to-income ratio

House price-to-disposable income ratio, deviation from long-term average, % ECB (DG Economics)
The lower threshold for the indicator is set close to an early warning model
threshold with balanced preferences between type I and type II errors.

RRE valuation measure,
econometric model

Deviation of actual house prices from model long-term equilibrium, %
For a detailed description of the methodology, see Financial Stability
Review, ECB, November 2015, Box 3:
Financial Stability Review
The lower threshold for the indicator is set close to an early warning model
threshold with balanced preferences between type I and type II errors.

ECB (DG Economics)

Lending indicators
Growth in loans to
households for house
purchases

Loans to domestic households for house purchases, 12-month growth, %
In combination with measures of real estate price growth and price
valuations, this provides early indications of the formation of a debt-fuelled
housing price bubble. The lower threshold for the indicator is set close to an
early warning model threshold with balanced preferences between type I
and type II errors.

Balance sheet items
(ECB SDW)

Loans to households for
house purchases relative to
peak prior to 2014

Ratio of current level of loans for house purchases to peak level of loans for
house purchases before 2014
The first threshold is arbitrarily set to 1 to flag countries where the stock of
mortgages reached levels above earlier peaks.

Balance sheet items
(ECB SDW)

Household loan spread

Spread on the lending rate for house purchase
This indicator captures the compression of lending spreads which might
relate to underpricing of risks and exuberant lending policies. The first
threshold is set at the 70th percentile of the cross-country distribution.
Before a weighted average is calculated using the respective loan volumes,
a reference rate is subtracted from the interest rates depending on their
maturities:
1 year: 3-month EURIBOR or 3-month money market rates
1 to 5 years : 3-year government bond yields if available
5 to 10 years: 7-year government bond yields if available, otherwise 10-year
government bond yields
10 years: 10-year government bond yields

Macroprudential database (ECB
SDW)
ECB MFI interest rate database

Household stretch
Household debt, % of GDP

This indicator captures households’ leverage and relates to the ability of
households to withstand shocks. The first threshold is set close to the precrisis average across countries.

MUFA and NFA (based on ESA
2010)

Household financial assetsto-debt ratio, %

This indicator captures the ability of households to withstand shocks by
comparing the financial wealth of households to debt. The first threshold is
set close to the pre-crisis average across countries.

MUFA and NFA (based on ESA
2010)

Debt service-to-income ratio
for households, %

This indicator captures debt servicing costs. The lower threshold for the
indicator is set close to an early warning model threshold with balanced
preferences between type I and type II errors.
For more details, see Drehmann, M., Illes, A., Juselius, M. and Santos, M.,
“How much income is used for debt payments? A new data base for debt
service ratios”, BIS Quarterly Review, September 2015
BIS Quarterly Review

ECB (DG/MF)

ESRB
Vulnerabilities in the EU residential real estate sector / November 2016
Annex B
Methodology – Horizontal method

155

Table B.2
Reference period for scoreboard observations
Reference period
Residential Residential
real estate price index
price
relative to
index, 12m peak prior
growth, %
to 2014

RRE
valuation
measure,
house
price to
income

Loans to
RRE
HH for
valuation
house
measure,
purchases,
12m
econometric
model
growth, %

Loans to
HH for HP
relative to
peak prior
to 2014

AT

31/03/2016

31/12/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/12/2015

BE

31/03/2016

30/09/2015

31/12/2015

31/12/2015

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/12/2015

BG

31/12/2014

31/12/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/03/2016

CY

31/03/2016

31/12/2015

31/12/2015

31/12/2015

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/03/2016

CZ

31/12/2014

31/12/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016

DE

31/03/2016

31/03/2016

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/12/2015

DK

31/03/2016

31/12/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/12/2015

EE

31/03/2016

31/12/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/03/2016

ES

31/03/2016

31/12/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/12/2015

FI

30/06/2015

30/06/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/12/2015

FR

31/03/2016

31/12/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/12/2015

GR

31/03/2016

31/03/2016

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/12/2015

HR

31/12/2015

31/12/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/03/2016

HU

30/09/2015

30/09/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2015 31/03/2016 31/12/2015 31/12/2015

IE

31/03/2016

31/03/2016

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/12/2015

IT

31/03/2016

31/12/2015

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/12/2015

LT

31/12/2015

31/12/2015

31/12/2015

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/03/2016

LU

31/03/2016

31/12/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/12/2015

LV

31/03/2016

31/12/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/03/2016

MT

31/12/2015

31/12/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/03/2016

NL

30/06/2016

31/03/2016

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/12/2015

PL

31/12/2015

31/12/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/12/2015

PT

31/12/2015

31/12/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/12/2015

RO

31/12/2015

31/12/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/03/2016

SE

31/03/2016

31/03/2016

31/03/2016

31/03/2016

30/06/2016

31/03/2016

SI

31/03/2016

31/12/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/03/2016

SK

31/03/2016

31/12/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016 01/01/2016 31/03/2016 31/12/2015 31/03/2016

UK

30/09/2015

30/09/2015

31/03/2016

31/03/2016

30/06/2016

31/03/2016

Country

ESRB
Vulnerabilities in the EU residential real estate sector / November 2016
Annex B
Methodology – Horizontal method

HH Loan
spread

HH debt,
% of GDP

HH
financial
assets to
debt, %

Debt
service to
income
ratio for
HH, %

31/03/2016 31/12/2015 31/12/2015

31/03/2016 31/12/2015 31/12/2015

31/03/2016 31/12/2015 31/12/2015

156

Table B.3
Robustness check: scoreboard without thresholds – the percentile rank approach
Indicators
Collateral Stretch
Residential real
estate
price
index,
12m
growth,
%

Residential price
index
relative
to peak
prior to
2014

RRE
valuation
measure,
house
price to
income

AT

0.84

1.00

BE

0.68

1.00

Country

BG
CY

0.50

CZ

Sum

Lending Indicators

RRE
valuation
measure,
econome
tric
model

Loans to
HH for
house
purchases,
12m
growth,
%

Loans to
HH for
HP
relative
to peak
prior to
2014

HH Loan
spread

1.00

0.86

0.62

1.00

1.00

0.89

0.42

1.00

0.73

0.52

0.40

0.35

0.38

0.24

0.29

0.94

0.78

Household Stretch

HH debt,
% of GDP

HH
financial
assets to
debt, %

Debt
service to
income
ratio for
HH, %

Average
rating
across
indicators

0.91

0.10

0.86

0.10

0.73

0.81

1.00

0.06

0.99

0.78

0.58

0.76

0.13

1.00

0.05

0.50

0.33

0.56

0.50

0.33

0.53

0.60

0.43

0.61

0.44

1.00

0.71

0.88

0.68

0.76

DE

0.96

1.00

0.80

0.56

1.00

1.00

0.87

0.03

0.99

0.03

0.72

DK

0.46

0.90

0.85

0.78

0.14

0.96

0.91

0.27

1.00

0.37

0.66

EE

0.27

0.85

0.71

0.46

0.93

1.00

0.93

0.46

0.77

0.25

0.66

ES

0.58

0.65

0.52

0.62

0.26

0.51

0.76

0.39

0.71

0.47

0.55

FI

0.34

0.97

0.88

0.75

0.22

1.00

0.80

0.99

0.39

0.84

0.72

FR

0.32

0.68

0.55

0.48

0.26

1.00

0.91

0.97

0.43

0.60

0.62

GR

0.30

0.24

0.06

0.28

0.26

0.64

0.94

0.13

0.47

0.77

0.41

HR

0.60

0.15

0.21

0.09

0.05

0.09

1.00

0.11

0.94

0.11

0.34

HU

0.82

0.61

0.43

0.28

0.44

0.30

0.95

0.39

0.74

0.42

0.54

IE

0.52

0.72

0.50

0.14

0.14

0.42

0.91

0.11

1.00

0.26

0.47

IT

0.23

0.61

0.42

0.38

0.86

0.74

0.11

0.89

0.58

0.53

LT

0.61

0.86

0.65

0.70

0.62

1.00

0.57

0.33

0.78

0.21

0.64

LU

0.68

0.97

1.00

0.83

0.34

1.00

0.93

1.00

0.34

0.86

0.80

LV

0.63

0.69

0.54

0.12

1.00

0.08

0.94

0.16

1.00

0.13

0.53

MT

0.84

1.00

0.76

0.20

0.24

1.00

0.60

0.48

0.62

0.40

0.61

NL

0.52

0.70

0.39

0.56

0.68

1.00

0.67

0.08

0.92

0.52

0.60

PL

0.79

0.42

0.38

0.05

0.02

0.96

0.93

0.92

0.49

0.56

0.55

PT

0.97

0.59

0.26

0.41

0.22

0.55

0.65

0.39

0.83

0.52

0.54

RO

0.88

0.50

0.33

0.15

0.60

1.00

0.84

0.13

0.84

0.05

0.53

SE

0.97

1.00

1.00

1.00

0.40

1.00

1.00

0.83

0.74

0.88

SI

0.68

0.52

0.34

0.20

0.35

1.00

0.19

0.48

0.64

0.32

0.47

SK

0.67

0.13

0.38

0.04

0.47

1.00

0.18

1.00

0.20

1.00

0.51

UK

0.74

1.00

1.00

0.74

0.45

0.94

0.54

0.71

0.47

0.73

EAA

0.51

0.88

0.65

0.49

0.31

1.00

0.55

0.70

0.64

EAM

0.51

0.88

0.65

0.49

0.31

1.00

0.55

0.70

0.64

ESRB
Vulnerabilities in the EU residential real estate sector / November 2016
Annex B
Methodology – Horizontal method

157

Annex C
Additional key indicators for focus countries

Table C.1
Additional key RRE market indicators for focus countries in the vertical analysis
Household stretch

DTI (%)

Collateral stretch

% variable
rate
mortgages:
new loans

PTI:
latest index
value

PTR:
latest index
value

Average
mortgage
maturity:
stock

LTV: new
loans

LTV: stock

% amortising
mortgages:
stock

AT

84.7

72.2

126.9

113.8

-

65.2 (*)

-

-

BE

102.8

3.6

104.6

102.2

-

62.3

21.4

95.0

DK

235.8

- (*)

97.3

100.8

49.7

96.0

27.2

49.1

EE

72.0 (*)

88.9

109.4

77.8

68.9

72.3

23.0

100.0

FI

112.2

96.9

96.9

88.8

-

-

-

-

LU

148.7 (*)

51.9

118.2

119.2

48.2

66.5

21.0

-

MT

94.4 (*)

73.0

81.4 (*)

-

-

75.1

26.7 (*)

-

NL

230.8

12.7

85.4

78.3

68.0

94.0

30.0

21 (*)

SE

167.2

- (*)

121.5

129.9

61.0

69.2

41.0

66.0

SK

46.7

4.0

93.6

104.7

-

74.0

-

-

UK

129.7

12.3

115.5

111.3

-

76.0 (*)

18.0

77 (*)

ECB SDW or
countries’
own
estimates.

ECB SDW
series:
average of
last 12
months, last
data for May
2016; or
countries
provided own
estimates

Nominal
house prices
to nominal
gross
disposable
income
(index: 2010
= 100);
OECD

Nominal
house prices
to nominal
rent (index:
2010 = 100);
OECD

Countries
provided
own
estimates

Countries
provided
own
estimates

Countries
provided
own
estimates

Countries
provided own
estimates
where
possible

Q1 2016

May 2015-16
average for
SDW data;
latest
available
country
estimates

Q1 2016

Q1 2016

Latest
available

Latest
available

Latest
available

Latest
available

Source
notes

Underlined data indicate a country’s own estimate rather than data from a common statistical source.
Full data sources and definitions are shown in Table C.3.
AT: survey-data refer to the average median of LTV ratios for new housing loans based on an OeNB sample of six Austrian banks. Data display a
relatively high degree of variance between banks.
DK: % of new loans with variable rates n/a; the % in stock 60%. LTV on new loans from “Report on Residential Real Estate”, ESRB, 2015.
EE: latest DTI from country self-assessment, value as at Q4 2015.
LU: DTI has been taken from country self-assessment.
MT: the measure of disposable income used in DTI and PTI estimates is based on the Central Bank of Malta’s estimates produced for the ECB’s
Broad Macroeconomic Projections Exercise; the PTI estimate uses the official index of transacted property prices in Malta; average maturity on new
loans only.
NL: with respect to mortgage loans that are not fully amortising, 45% are partly amortising and 34% are not amortising.
SE: % of new loans with variable rates n/a; % in stock 68%.
SK: latest DTI from country self-assessment; LTV on new loans from “Report on Residential Real Estate”, ESRB, 2015.
UK: 76.0% is the median LTV on new loans in Q1 2016; 98% of new loans are amortising.

ESRB
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Annex C
Additional key indicators for focus countries

158

Table C.2
Additional key RRE market indicators for focus countries in the vertical analysis
DTI
Latest value
(%)

1-year
change (%)

AT

84.7

BE

102.8

DK
EE

PTI
3-year
change (%)

Distance to
peak (%)

Latest index
value

1-year
change (%)

3-year
change (%)

-1.2

0.1

-5.0

126.9

11.8

14.2

0.0

1.9

10.1

0.4

104.6

2.0

0.1

-0.4

235.8

-7.6

-12.9

-13.2

97.3

-0.7

3.5

-25.1

72.0

-1.4

-6.9

-24.8

109.4

-5.0

9.4

-39.5

FI

112.2

2.3

5.2

-0.2

96.9

1.6

-1.3

-33.6

LU

-

-

-

-

118.2

5.2

10.7

2.5

MT

94.4

-0.1

1.2

-1.8

81.4

-2.5

-6.5

-24.2

NL

230.8

-2.2

-4.9

-6.2

85.4

2.0

1.5

-19.8

SE

167.2

2.8

8.1

0.1

121.5

8.3

25.3

-0.9

SK

46.7

5.2

18.9

0.0

93.6

1.7

2.0

-28.2

UK

129.7

-0.4

-1.9

-11.6

115.5

4.8

16.3

1.4

Source
notes

ECB SDW or countries’ own estimates (a country’s own
estimates are underlined as not directly comparable with
SDW series)

Distance to
peak (%)

Nominal house prices to nominal gross disposable income
(index: 2010 = 100), OECD; or countries provided own
estimates (own estimates shown in grey as not directly
comparable with SDW series)

Full data sources and definitions are shown in Table C.3.
Distance-to-peak value is measured as: (Current measure - Peak measure since start of series excluding latest quarter)/Peak measure since start of
series excluding latest quarter.
The DTI series starts at the earliest in Q1 2000 (depending on the country) and ends in Q1 2016; the PTI series starts at the earliest in Q1 1970
(depending on the country) and ends in Q1 2016.

ESRB
Vulnerabilities in the EU residential real estate sector / November 2016
Annex C
Additional key indicators for focus countries

159

Table C.3
Sources and definitions of main indicators
Indicators

Description

Data source

Latest date

DTI

Ratio of household debt to the
annual sum of household gross
disposable income

MUFA and NFA (based on ESA
2010)

Q1 2016

% variable rate mortgages: new
loans

12-month average share of new
mortgages with up to one year
interest rate fixation period as a %
of total new mortgages

MFI interest rates (MIR)

May 2016

PTI

Nominal house prices to nominal
gross disposable income (index:
2010 = 100)

OECD

Q1 2016

PTR

Nominal house prices to nominal
rent (index: 2010 = 100)

OECD

Q1 2016

LTV: stock

Average loan-to-value ratio for
mortgagors

Latest data from country selfassessment or teleconference with
country
Possibility of slightly different
definitions for the figures provided
by each country

Latest available

LTV: flow

Average loan-to-value ratio for
mortgagors

Latest data from country selfassessment, from teleconference
with country or from “Report on
Residential Real Estate”, ESRB,
2015 (collected for that report via a
questionnaire)
Possibility of slightly different
definitions for the figures provided
by each country

Latest available

Average mortgage maturity: stock

Average maturity on mortgage
loans

Latest data from country selfassessment or from “Report on
Residential Real Estate”, ESRB,
2015.

Latest available

% amortising mortgages: stock

Share of amortising loans as a %
of total loans

Latest data from country selfassessment or teleconference with
country
Possibility of slightly different
definitions for the figures provided
by each country

Latest available

ESRB
Vulnerabilities in the EU residential real estate sector / November 2016
Annex C
Additional key indicators for focus countries

160

Annex D
Overview of assessments by third parties 179
Country

Institution

Publication

Statement

Austria

OECD

OECD Economic Surveys,
Austria, July 2015, Overview

The share of variable-rate loans is considerably larger in Austria than in other
euro area countries and has increased further recently. This would make
households more vulnerable to interest rate increases. In addition, a
considerable, though declining, share of loans is still denominated in foreign
currencies. (p. 17)

Austria

IMF

2016 Article IV Consultation,
10 February 2016

Corporate and household debt levels are comparatively low, but household
loans in Swiss francs remain a concern. Corporate and household debt is
below the euro area average. However, the share of Swiss franc loans in
total household mortgage loans remains around 20 percent even after a
gradual decline since 2007.
(pp. 15-16)
Real estate price dynamics have moderated, although there are signs of
overvaluation in Vienna. Annual price increases have dropped below 5
percent recently. On the back of strong price dynamics in previous years, the
OeNB’s fundamentals-based indicator still suggests an overvaluation of
about 20 percent in Vienna. (p. 16)

Austria

EC

Country Report Austria 2016,
26 February 2016

Foreign-exchange denominated loans to Austrian households also continue
to represent a source of vulnerability. Swiss franc denominated loans
account for roughly 96% of foreign currency denominated loans and were very
popular in Austria before 2008. About 70% of the total foreign currency loans
granted by banks to Austrian households were bullet loans, most of them
linked to repayment vehicles, i.e. an investment fund used to repay the
principal of the loan at the end of the term, which are sensitive to financial
market developments. (p. 15)

Belgium

OECD

OECD Economic Surveys,
Belgium, February 2015,
Overview

However, the large increase in house prices of the past decade, fuelled by
generous tax conditions, has led to overvaluation. The rental market is small,
with long waiting lists for social housing and tenants in the private market
spending an increasing share of their income on housing. (p. 4)
Domestic risks stem from the vulnerabilities related to high public debt
and historically high house prices. (p. 11)
However, the steep increase in house prices before the crisis and some
increase afterwards put market access for first-time buyers under pressure.
Housing affordability is also deteriorating for the poor, as demand for
social housing is not met by supply and even the cheaper segment of the
private rental market has become overpriced. (p. 32)

Belgium

IMF

2016 Article IV Consultation,
2 March 2016

However, staff analysis does not suggest a major overvaluation, as past
price trends were broadly in line with borrowing cost, demographic and
income developments. (p. 12)
Recent strong household credit growth could be a cause for concern. (p.
22)
Low risk - Rapid and disruptive housing price correction. (p. 41)

Denmark

OECD

OECD Economic Surveys,
Denmark, May 2016, Overview

Negative interest rates are contributing to the risk of building-up a new bubble
in the housing market and may be encouraging excessive risk-taking by
households and the financial sector. (p. 4)
Monetary conditions are very accommodative and automatic stabilisers in the
housing market cannot work fully (p. 5).
High household debt poses vulnerabilities. (p. 5)
Private rental market is underdeveloped. (p. 5)
Households are among the most indebted in the OECD, though they also
hold very large pension assets. Most mortgages have variable interest rates,
and interest-only periods are also common. Household exposure to rising
interest rates, house-price fluctuations and losses in income are therefore of
concern. (p. 15)

Denmark

IMF

Denmark: Staff Concluding
Statement of the 2016 Article
IV Mission,
4 May 2016

Denmark

EC

Country Report Denmark 2016 Over the last three years the recovery of the housing market has gathered
steam in certain segments of the market, but has slowed down somewhat

179

Rapid house price increases call for vigilance. Fuelled by historically-low
interest rates, house prices have risen rapidly in recent periods –especially for
flats and in Copenhagen.

The statements in the tables in this section are extracted from the cited publications. The ESRB has added the emphasis to
the text in bold.

ESRB
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Overview of assessments by third parties178F

161

in the second half of 2015. The strongest price increase was registered in the
large cities, and especially in the capital region. However, on average, Danish
house prices are still significantly lower than their peak in 2006. (p. 1)
The risks stemming from high household indebtedness seem contained
and the financial sector is solid. High household debt is a structural feature
of the Danish economy and is related to the specific mortgage system.
Households in Denmark appear to be resilient to market shocks, i.e. their debt
is backed up by a strong financial position, with assets exceeding gross debt.
(p. 2)
Property sales have picked up significantly since early 2013, and in the
capital region sales of owner-occupied flats are currently close to the peak
seen in 2005. (p. 6)
Housing tax structure affects house price trends. Certain parts of the
housing market, i.e. owner-occupied flats in larger towns and cities, and in
particular the Copenhagen area, have recently witnessed strong and possibly
unsustainable price increases. (p. 12)
Estonia

OECD

OECD Economic Surveys,
Estonia, January 2015,
Overview

Persistently low long-term interest rates could result in the re-emergence of
risks in the domestic housing market. (p. 11)

Estonia

IMF

Republic of Estonia: 2015
Article IV Consultation;
14 December 2015

Risks from the domestic housing market are not acute, considering that
recent price increases are not credit driven and price-to-income ratios remain
much below previous peaks. (p. 18)

Estonia

EC

Country Report Estonia 2016

While house price increases have been strong they are still in line with
income developments. This reflects the strong link between the housing
demand and wage growth in recent years. (p. 2)
According to different valuation gap models, house prices have increased in
recent years to close to a notional ‘overvaluation’ estimate, but have not
yet significantly passed it. […] Should the present price increase persist,
however, house prices would soon be overvalued. (p. 29)
Estonia is characterised by two possible signs of domestic overheating: the
rapidly rising unit labour costs and housing prices. Both pose risks, as they
expose the country to possible competitive losses and a disorderly correction
with harmful implications for the real economy. (p. 37)

Finland

OECD

OECD Economic Surveys,
Finland January 2016,
Overview

The main domestic financial vulnerability relates to high household debt,
even though it is lower than in the other Nordics. High loan-to-value (LTV)
mortgages are common in Finland (FIN-FSA, 2012), and most mortgages
carry variable interest rates. Heavily indebted households are vulnerable to
higher interest rates, losses in income or falls in housing prices. At the same
time, there is no sign of a housing bubble, as housing prices have been
broadly flat for more than a decade. (p. 9)

Finland

IMF

Finland: 2015 Article IV
Consultation;
17 November 2015

Meanwhile, the housing market has cooled and standard metrics suggest that
average house prices are broadly in line with fundamentals. (p. 13)
Prolonged stagnation and higher unemployment could also conceivably cause
house prices to decline and prompt deleveraging by the most highly indebted
households. (p. 13)

Finland

EC

Country Report Finland 2016

Households could suffer from an abrupt fall in house prices, but such a
scenario is unlikely as relative house prices are close to their long term
averages. (p. 7)
On aggregate, households have not started to deleverage as they have
benefited from a prolonged period of favourable lending conditions,
including exceptionally low interest rates and mortgage repayment holidays.
(p. 22)

Luxembourg OECD

OECD Economic Surveys,
Luxembourg, March 2015,
Overview

Luxembourg’s supply of housing may be falling short of demand, as rising real
house prices indicate. (p. 33)

Luxembourg IMF

Luxembourg: 2016 Article IV
Consultation, 16 May 2016

Banks’ exposure to the real estate market is a risk to watch closely.
Rising house prices largely reflect strong demand outstripping supply, partly
because of supply bottlenecks and zoning regulations. (p. 10)
On the housing market and in light of ever rising housing prices, the
authorities should explore the effectiveness of recent measures in containing
risk and whether further macro-prudential measures such as limits to loan-tovalue ratios in addition to those already taken in 2013 would be appropriate.
(p. 16)

Luxembourg EC

Country Report Luxembourg
2016

House price pressures emerge from both the supply and demand side.
On the supply side, land availability and administrative procedures seem to
represent a bottleneck to the creation of new housing units. On the demand
side, high population and employment growth, as well as, to a lesser extent,
tax policies encouraging ownership push up prices. (p. 2)
Low interest rates and easing of financial conditions have supported
steady growth of mortgage loans, which represents a large part of
household indebtedness (in 2014 household debt amounted to 56.7% of GDP,
compared with 59.6% in the euro area). The surge in house prices is likely to
have exacerbated this trend, with households having to ask for higher loans.
(p. 8)
Indeed, suboptimal administrative performance on building permit issuance
may feed into market imperfections and imbalances and contribute to

ESRB
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Annex D
Overview of assessments by third parties178F

162

house price inflation. (p. 21)
Faced with rather rigid housing supply, a great part of the tax subsidy is
likely to be capitalised into house prices. (p. 23)
Malta

IMF

Malta: 2015 Article IV
Consultation, 6 January 2016

Netherlands

OECD

OECD Economic Surveys,
Netherlands, March 2016,
Overview

The private rental market falls short of rising demand. (p. 5)

While the default rates on mortgages and household indebtedness have been
low, there has been a rapid increase in mortgages, there is a relatively high
overall exposure to real estate, and there has been a pick up in real estate
prices – fuelled by a combination of factors, such as tax incentives for first
time buyers, increase in rental demand stemming from the international
investor program, increased migration, and the ECB’s QE.
Core domestic banks are significantly exposed to the housing market.

Indicators of potential macro-financial vulnerabilities have abated significantly
since the crisis, although, at nearly 120% of GDP, gross household debt is
one of the highest in Europe, owing to high mortgage debt, posing a
vulnerability in the event of a financial crisis. (p. 14)

Netherlands

IMF

Netherlands: 2015 Article IV
Consultation,
11 February 2016

This is an important distortion as large amounts of savings are detracted from
potentially productive investments to further inflate house prices. (p. 10)

Netherlands

EC

Country Report Netherlands
2016

The housing market has contributed to a range of macroeconomic
imbalances. (p. 1)
The tax treatment of owner-occupied housing remains generous and
encourages mortgage borrowing. (p. 3)
Moreover, given the low elasticity of housing supply, strong fiscal incentives
to home ownership push up house prices, thereby fuelling mortgage debt
growth and worsening affordability. (p. 7)
Households’ financial distress has risen in the past decade. The
increasingly high level of debt has led to more households finding it difficult to
repay their loans. (p. 26)

Slovakia

IMF

Slovak Republic: 2015 Article
IV Consultation,
14 January 2016

Recent macroprudential recommendations by the National Bank of Slovakia
(NBS) have not slowed household credit growth, which is expanding by
about 12 percent year-on-year, although household debt remains low
compared to peers. (p. 5)
On the domestic side, rapid household credit growth could lead to
financial sector risks. (p. 5)

Slovakia

EC

Country Report Slovakia 2016

In the medium term, price pressures in the housing sector might pick up due
to several structural factors. Potential demand for housing space is ample.
(p. 7)

Sweden

OECD

OECD Economic Surveys,
Sweden,
March 2015, Overview

Household debt and dwelling prices have soared over the past decade.
The housing price-to-income ratio is about 20% above its long-term average,
suggesting moderate overvaluation. This creates risks for households and
the wider economy. (p. 17)
Swedes have a long history of paying only interest on home loans and a large
share of households (close to 40% in 2013) do not pay down mortgage
principal. (p. 17)

Sweden

IMF

Sweden: 2015 Article IV
Consultation, 2 December
2015

Rapid housing price increases associated with rising household
indebtedness. (p. 4)
The housing market shows imbalances, with double-digit price gains as the
urban population outpaces construction, pushing up household debt from
already high levels. Housing supply is constrained by construction
impediments and rent controls while demand is bolstered by population
growth and urbanization, rising income and financial savings, and historically
low interest rates. (p. 6)
However, house prices could continue rising from already high levels.
(p. 8)
The experiences of Denmark and the Netherlands after the global financial
crisis are indicative, although household debts and house price deviations
appear to have been greater in these countries in 2008 than yet seen in
Sweden. (p. 8)

Sweden

EC

Country Report Sweden 2016

Structural inefficiencies on the housing market not only impact investment
negatively but contribute to an increase in house prices and could hamper
labour market mobility. Surging house prices are further increasing private
indebtedness from already record high levels making the economy more
vulnerable to shocks. (p. 1)
The high level of household indebtedness in Sweden has been identified as
posing an ongoing risk for macroeconomic stability. (p. 2)
Sweden is one of the EU countries most exposed to vulnerabilities on
the housing market. Persistent overvaluation and surging house prices
coupled with high and rising household indebtedness, essentially driven by
credit for house purchases, increasing debt-to-income ratios and high
leverage in banks reflect elevated risks in this respect. Swedish house
prices are above their fundamental levels, due to supportive taxation policy
and structural inefficiencies in the housing market. […] Overvalued house
prices entail risks of a disorderly and harmful correction, with a potential

ESRB
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Annex D
Overview of assessments by third parties178F

163

impact on the banking sector and the real economy. (p. 2)
The impact of a possible house price correction in the context of high
household indebtedness is a growing concern. The regulatory capital
adequacy ratios for Swedish banks are high, but the actual share of capital in
banks’ balance sheet remained at a relatively low level in recent years. (p. 2)
UK

OECD

OECD Economic Surveys,
United Kingdom,
February 2015, Overview

In addition, house prices have increased rapidly and may create risks to
financial stability in the case of a downward adjustment. (p. 4)
The recovery in the housing market has been marked by large house
price increases, particularly in London, raising homeowners’ wealth, but also
reducing affordability for first-time buyers and contributing to higher household
indebtedness. (p. 11)

UK

IMF

United Kingdom: 2015 Article
IV Consultation, 24 February
2016

Housing and mortgage markets have decelerated somewhat over the last
year, and lenders have become more resilient. Nonetheless, house-price
growth continues to outpace income growth, and household leverage
remains high by historical standards. A leverage-driven re-acceleration of the
market would further increase households and banks’ vulnerabilities to houseprice, income, and interest-rate shocks. (p. 8)
High house prices result in some households taking on high leverage,
posing financial stability risks. (p. 20)
A rapid rise in house price-to-income ratios driven by increased leverage
would raise the vulnerability of banks and households to adverse shocks to
house prices, income, and interest rates. (p. 40)

UK

EC

Country Report UK 2016

Developments in the housing market have posed challenges but more
recently housing market indicators have varied. (p. 1)
House price levels remain high, and affordability has deteriorated as growth
in house prices exceeds that in nominal disposable income. (p. 2)
However, over the medium term, demand continues to outstrip supply in
the housing market. As a result, house prices are likely to continue to
increase, as is household indebtedness. This leaves the household sector and
the wider economy more exposed to risks over a longer period of time than
would otherwise be the case. (p. 2)
Activity in the housing market has risen to its highest levels since the
recession. Starts and completions increased and demand has been
supported by a rise in mortgage approvals. (p. 8)
For the fifth consecutive year, high levels of private sector indebtedness have
been identified as potentially posing risks to the stability of the
household sector. (p. 14)
The risks need to be assessed in the context of the recent pick up in house
price growth and the high level of house prices, the high level of household
indebtedness and the medium term gap between demand and supply for
housing. (p. 14)
As measured by the house price to income ratio, affordability has
deteriorated markedly since 2012 as house price growth has risen and
exceeded growth in household disposable income. (p. 15)
Forward indicators of house prices are mixed but some key indicators suggest
that the renewed momentum in house price increases will continue.
(p. 17)

ESRB
Vulnerabilities in the EU residential real estate sector / November 2016
Annex D
Overview of assessments by third parties178F

164

Proposals made by international institutions regarding policy issues in
the real estate market
Country

Institution

Document

Policy proposal

Austria

IMF

IMF Executive Board
Concludes 2015 Article IV
Consultation with Austria,
Press Release No. 16/58,
12 February 2016

Directors also underscored the need for banks to proactively mitigate risks
from their cross-border exposures and domestic mortgage loans in foreign
currency. They supported an expansion of the macroprudential toolkit with
respect to real estate-specific instruments.
Financial repair has advanced considerably, but needs to be completed. The
focus should be on raising bank capital and addressing remaining risks
stemming from exposure to some difficult CESEE markets and domestic
Swiss franc loans. Expanding the macroprudential toolkit with real estatespecific instruments would limit risks to banks’ asset portfolios if real estate
price bubbles emerge. Wind-down units of resolved banks need to complete
the asset disposal process efficiently.
However, the macroprudential toolkit still lacks sector-specific
instruments, such as caps on loan-to value (LTV), debt-to-income (DTI),
and debt-service-to-income (DSTI) ratios for mortgage loans. The
macroprudential toolkit should be further strengthened by introducing
sector-specific caps on LTV and DTI/DSTI ratios, possibly regionally
differentiated. While not binding at present, such caps would be useful
if house prices pick up strongly in parts of the country. (p. 17)

Belgium

OECD

OECD Economic Surveys,
Belgium,
2015

Housing affordability is also deteriorating for the poor, as demand for social
housing has not been met while the private rental market has become
expensive. As a result, access to housing is at risk of becoming less
equitable if the young and poorer people are priced out. Affordability for
poorer people could be improved by expanding the regional rental allowance
schemes. In parallel, scaling down the disproportional support for
homeownership would free up public resources and reduce the bias towards
homeownership. (p. 49)

Belgium

IMF

Belgium:
2016 Article IV Consultation
– press release and staff
report

Given the strong growth in mortgage lending, Directors recommended
vigilance and proactive supervision, including consideration of targeted
prudential measures to limit overexposures of vulnerable borrowers.
(p. 2)
Recent strong household credit growth could be a cause for concern. Risks
to bank’s balance sheets are mitigated by the prevalence of owneroccupancy and of fixed-rate mortgages, as well as a default law that protects
against selective default, and more generally by a relatively strong net asset
position of households. In addition, recent prudential measures raising risk
weights on mortgages appear to have borne fruit. However, a significant
share of loans still have relatively high loan-to-value and/or debt-service-toincome ratios, suggestive of pockets of vulnerabilities, particularly in the
young and low to middle income borrowers, that warrant continued vigilance.
Staff thus recommended considering more targeted actions to limit
overexposures of vulnerable groups (for example, additional risk weights
or caps on loan-to-value ratios or limits on debt-service-to-income ratios).
Staff also cautioned against banks’ overreliance on the mortgage business.
(p. 23)
Following the increase in capital requirements on mortgage lending in 2014,
additional macroprudential measures could be introduced while also working
on the supply side of the housing market to alleviate price pressures. (p. 41)

Denmark

OECD

OECD Economic Surveys,
Denmark,
May 2016

Negative interest rates are contributing to the risk of building-up a new bubble
in the housing market and may be encouraging excessive risk-taking by
households and the financial sector. However, credit growth remains
subdued. To mitigate future risks, macro-prudential tools should be
extended across the whole country and tax policy of the property
market needs to play its counter-cyclical role. Also, the debt-bias in
favour of housing and credit should be lowered, in order to limit the
vulnerability of households to rising interest rates. (p. 4)
Reform property taxation, including by decreasing mortgage interest rate
deductibility and regularly updating valuations in order to establish neutrality
across different asset classes. Encourage mortgage institutions to strengthen
the use of debt-service-to-income ratios. Give consideration to extending
some of the locally targeted “Best practices” introduced by the regulator for
granting a mortgage in hotspot areas to the whole country. Support a bigger
private rental housing market by easing rent regulation while striking a
balance between landlord and tenant protection. (p. 5)

Denmark

IMF

Denmark: Staff Concluding
Statement of
the 2016 Article IV Mission,
4 May 2016

Rapid house price increases call for vigilance. Fuelled by historically-low
interest rates, house prices have risen rapidly in recent periods – especially
for flats and in Copenhagen. While a recent slowdown in the volume of
housing transactions might herald an impending softening, the market bears
close watching since a continuation of the uptrend would soon bring real
house prices in these segments back to pre-crisis levels. For the moment,
risks are mitigated by the localized character of the steepest price increases
and the absence of an attendant rapid build-up in household debt. However,
past experience suggests that bubbles can form and spread quickly.
Moreover, with high shares of “interest only” and variable rate loans,
households are already exposed to substantial interest rate risk.
Action across several policy areas would help contain the build-up of housing
risks. We welcome the introduction of the DFSA’s “Supervisory Diamond for
Mortgage Credit Institutions (MCIs),” which addresses risks related to
variable rate and interest only loans. In addition, the recent establishment of
the “Seven Best Practices” should strengthen risk management practices of
mortgage lenders in areas with rapid house price increases. The introduction
of a five percent cash down payment requirement for house purchases is
also a step in the right direction. However, more can be done and early

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action would help the authorities stay ahead of the curve.
Additional macroprudential tools should be developed. The preparation of
an adequate macroprudential “toolbox” is important to ensure that
measures can be implemented without delay when needed. In
particular, we would suggest considering limits on the debt-to-income
ratio, which would help keep household debt and debt service capacity
in check, especially in a context where house prices rise faster than
incomes. The authorities should also consider raising the new minimum down
payment requirement to at least 10 percent to increase households’ buffer in
case of adverse house price shocks. These measures would complement the
existing MCI supervisory diamond as they help protect households (as
opposed to bank portfolios) and address risks from loans by commercial
banks (as opposed to MCIs only). This would also help ensure that risks are
not just shifted from the mortgage institutions to the banks. If regional market
conditions continue to diverge, consideration could be given to applying
policies with different stringency across regions.
More fundamentally, the present would be a good time to tackle longstanding
housing supply issues and reduce adverse incentives from taxation.
Improving zoning regulations could help alleviate supply constraints while
easing Denmark’s tight rental market regulations would facilitate more
efficient use of the existing housing stock. On the tax side, the procyclical
valuation freezes for land and property taxes should be ended and we
strongly welcome the authorities’ intention to transition to a new housing
valuation system, which will be discussed in the autumn.
Estonia

IMF

Republic of Estonia: 2015
Article IV Consultation –
press release, staff report
and informational annex

A comprehensive set of macroprudential tools is operational – maximum
loan-to-value and debt-service-to-income ratios have already been set,
though at currently barely binding levels. These tools also apply to foreign
branches. Oversight of consumer lending companies is being strengthened
through a licensing requirement from March 2016. (p. 18)

Finland

OECD

OECD Economic Surveys,
Finland,
January 2016

Two policy measures will reduce risks. Mortgage interest tax deductions are
being cut in steps; and from June 2016 a maximum LTV ratio of 90% (95%
for first-time buyers) will be imposed. Housing loans account for about 60% of
bank lending and risk weights computed through banks’ internal models
range between 6 and 13%, compared to 35% under the standardised
approach. There may be a case for introducing minimum risk weights on
mortgages, as in Norway and Sweden, and to encourage harmonisation of
risk-weight calculations across banks (Bank of Finland, 2015a). (p. 9)

Finland

IMF

Finland: 2015 Article IV
Consultation – press
release, staff report,
informational annex and
statement by the Executive
Director for Finland

Directors commended the authorities for introducing a new macroprudential
policy framework and implementing the EU’s Bank Recovery and Resolution
Directive. They noted that there is scope to strengthen the macroprudential
framework further, including through the introduction of a systemic risk buffer.
They also highlighted the importance of enhancing regional cooperation on
financial stability, supervisory, and bank resolution issues.
There is scope to further strengthen the macroprudential toolkit, including
adding a systemic risk buffer (SRB), as recommended by an internal study
group. Adding this optional CRD instrument would better align Finland with
the regulatory standards that its large foreign banks face in their home
jurisdictions. In view of banks’ increasing reliance on wholesale funding,
which creates potential funding and liquidity risks, the authorities should
implement the Basel III net stable funding ratio and liquidity coverage ratio
requirements as soon as is feasible. (p. 14)
Full implementation of the macroprudential policy toolkit will help reduce
vulnerabilities in the medium-run. Banks with potentially significant credit and
funding risks should be pushed to improve buffers in the short-run. If financial
market stress materializes, the ECB should provide ample liquidity. Full
adoption of the macroprudential toolkit and introduction of the systemic risk
buffer to bolster the largest banks’ ability to absorb losses. (p. 28)

Luxembourg

IMF

Luxembourg: 2016 Article
IV Consultation – press
release, staff report,
informational annex and
statement by the Executive
Director for Luxembourg

On the housing market and in light of ever rising housing prices, the
authorities should explore the effectiveness of recent measures in
containing risk and whether further macro-prudential measures such as
limits to loan-to-value ratios in addition to those already taken in 2013
would be appropriate. (p. 16)
Risks in the real estate market should continue to be closely monitored.
Steadily rising house prices appear to mainly reflect supply bottlenecks
against a growing demand. The authorities should explore the effectiveness
of recent macro-prudential measures in containing risks and whether further
measures such as limits to loan-to-value ratios are appropriate. (p. 25)

Malta

IMF

Malta: 2015 Article IV
Consultation,
6 January 2016

While the default rates on mortgages and household indebtedness have
been low, further consideration should be given to precautionary
measures, such as loan-to-value (currently at 74 percent for residential and
69 for commercial in 2014) and debt-to-income ratios, given the rapid
increase in mortgages, relatively high overall exposure to real estate, and
pick up in real estate prices. (p. 13)

Netherlands

OECD

OECD Economic Surveys,
Netherlands,
2016

Since 2013, amortisation of new mortgages has become a precondition for
mortgage interest deductibility, which should increase amortising mortgages
over time as before most of the mortgage portfolio was not amortized
regularly (that is, the principal was not paid down in instalments). Also, the
maximum tax rate at which mortgage interest can be deducted is being
lowered, but only very gradually from 52% to 38% between 2014 and 2042.
Other reforms include gradual cuts in the maximum loan-to-value ratios to
100% in 2018, reductions in loan-to-income ratios to offset higher lending
capacity driven by lower interest rates, and decreases in the maximum value
of a mortgage eligible to public guarantees (insuring against residual liabilities
left after a sale of a property). (p. 14)
Support the supply of rental housing by further limiting strict rent regulation in
the private market. (p. 5)

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Netherlands

IMF

Netherlands: 2015 Article IV
Consultation – press
release, staff report and
statement by the Executive
Director for the Kingdom of
the Netherlands

The authorities are reducing the maximum loan-to-value (LTV) ratio for
mortgage loans by one percentage point per year until it reaches 100 percent
in 2018, with no further plans beyond that date. The 2014 Article IV
consultation urged a further and faster reduction beyond 2018. In May 2015,
the Financial Stability Committee’s (FSC) recommended reducing the LTV by
one percentage point a year through 2028 when it would reach 90 percent.
The current policies of gradually reducing the LTVs ratios on new mortgages
to 100 percent by 2018 and allowing MID only for new fully amortizing loans
are steps in the right direction to mitigate housing risks. The prospective
reinstatement of the higher gift tax exemption is also welcome for reducing
mortgage debt. (p. 15)
Further improvement to the framework for risk management and resolution
are needed. Accelerate the pace of LTV reduction to reach 80 percent and
clarify [shortly] the path of LTV after 2018. (p. 38)

Slovakia

OECD

OECD Economic Surveys,
Slovak Republic,
November 2014

To develop the rental housing market, phase out support to home ownership
and expand means-tested rental housing allowances. (p. 3)
Some steps have been taken since January 2014 to promote rental housing
by providing loans with subsidised interest rates to the private sector
acquiring rental housing, targeted at those with low-income and in dynamic
economic areas. (p. 24)

Slovakia

IMF

Slovak Republic: 2015
Article IV Consultation –
press release, staff report
and statement by the
Executive Director for
the Slovak Republic

The banking sector has sound capital and liquidity buffers, and household
debt remains limited. Nonetheless, rapid credit growth among households
calls for further strengthening of macroprudential measures and a
vigilant approach should fast credit expansion continue and broaden.
Recent macroprudential recommendations by the National Bank of Slovakia
(NBS) have not slowed household credit growth, which is expanding by about
12 percent year-on-year, although household debt remains low compared to
peers. (p. 5)
Lowering the LTV limit: With the planned transposition of its macroprudential
recommendations into law, the LTV limit should be lowered from 90 to 85
percent, thus better aligning housing loan regulation with that of peers.
Introducing a debt-to-income ratio (DTI): The NBS should use authority under
the planned law to issue clear guidance on a maximum ratio for overall debtto-income of borrowers to enhance the effectiveness of the LTV limit.
Applying a counter-cyclical capital buffer: If above-trend credit growth
continues and broadens to the corporate sector, the adoption of a countercyclical capital buffer of at least 0.5 percent would be warranted.
Adopt more tailored supply-side measures to address real-estate-related
exposures: Raising credit risk weights and imposing stricter loss-givendefault assumptions on real estate-related exposures would raise the cost of
mortgage loans without affecting non-financial corporate borrowing.
Implementation of the new European standards for loan classification would
help, as would mandatory verification of external appraisals by lenders to
avoid inflated collateral valuations. (p. 18)
Additional macroprudential measures would help guard against risks
from rapid credit growth. Although household debt is relatively low and
banks enjoy sound capital and liquidity buffers, to limit financial stability risks,
the LTV limit should be lowered and clear guidance should be issued on a
maximum DTI ratio. If above-trend credit growth continues and broadens to
the corporate sector, a counter-cyclical capital buffer of at least 0.5 percent
would be warranted. In the near term, more targeted measures on real
estate-related exposures should be considered. (p. 21)

Sweden

OECD

OECD Economic Surveys,
Sweden,
March 2015

Macro-prudential policy is being reinforced to prevent the build-up of financial
imbalances, not least an unsustainable increase in household debt, as
interest rates stay low. (p. 4)
Continue to implement macro-prudential policies to contain the risks related
to rising household debt. Consider phasing out mortgage interest
deductibility. (p. 5)
The authorities have acted to improve the resilience of the financial system
by strengthening the institutional framework for financial regulation and
supervision, requiring stronger capital and liquidity buffers and implementing
macro-prudential measures. (p. 16)
A cap of 85% on mortgage loan-to-value ratios was introduced in 2010.
Minimum capital risk weights on mortgages were increased to 15% in 2013
and will rise to 25% in 2015. Swedes have a long history of paying only
interest on home loans and a large share of households (close to 40% in
2013) do not pay down mortgage principal (Finansinspektionen, 2014b). The
FSA will present a proposal to make holders of new mortgages repay capital
until the outstanding loan is down to 50% of the initial value of the property,
which is welcome. (p. 17)
The impact of the measures being implemented should be monitored
closely and further action should be envisaged if growth in household
debt picks up. Structural measures to improve the functioning of the housing
market could help moderate the increase in household debt, which is partly
driven by high housing prices, although reverse causality is also at play. Such
measures could include streamlining land-use planning and zoning
regulations and increasing incentives for municipalities to allow building to
improve supply responsiveness, limiting the tax bias in favour of homeownership (preferably by phasing out mortgage interest deductibility) and
easing rental market regulations to foster a more balanced tenure mix (Adalet
McGowan, 2013). (p. 18)

Sweden

IMF

Sweden:
2015 Article IV Consultation
– press release, staff
report, informational annex
and statement by the
Executive Director for
Sweden

The authorities are monitoring housing market and household debt
developments situation closely. At this juncture, they favour assessing the
impact of amortization requirements before taking further steps given
uncertainty around the impacts of macroprudential measures. A DTI limit is
among a number of tools that could be considered. (p. 17)
The long process of adopting amortization regulations should be completed
to cement the changes in amortization culture. But the FSA’s legal mandate
clearly needs to be strengthened to give it access to a range of

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macroprudential tools to address risks in a timely and efficient way. Although
such measures cannot substitute for housing supply reforms, they can
usefully moderate vulnerabilities from potential further rapid house price
increases. (p. 22)
Preventively, reduce vulnerabilities in the housing market through
macroprudential measures, phasing out tax incentives, and enhancing
housing supply. In the event, provide monetary stimulus and funding support
to banks. (p. 23)
UK

OECD

OECD Economic Surveys,
United Kingdom,
February 2015

Macro-prudential regulation should act to prevent financial crises, notably by
trying to head off the build-up of imbalances linked to credit cycles, which last
longer and have higher amplitude than business cycles (Haldane, 2014). It is
important that decision making about the size of the counter-cyclical capital
buffer and the timing of its implementation be supported by a range of
indicators, and such multifaceted approach is currently being developed. (p.
40)
In June 2014, the Financial Policy Committee capped loans carrying loan-toincome ratio of above 4.5 to 15% of banks’ new residential mortgages, which
should ward off risks of significant rise in the number of highly indebted
households. The Committee also asked the government for new powers to
cap loan-to-value ratios and debt-to-income ratios for mortgages. The share
of interest-only mortgages (principal repayment is postponed to the maturity
of the mortgage) in new loans has been falling steadily since the crisis, and is
now about 20% of new mortgages, which is welcome. Raising risk-weights
would reinforce this trend and prevent a weakening of underwriting standards
should the risk appetite for such loans increase. (p. 41)
Sustainable financing of the economy and greater financial stability should be
achieved by sound regulation, ensuring high capital requirements for
systemically important banks, improving banks’ resolvability and fine-tuning
the use of countercyclical measures. Data should be collected on a wider set
of financial institutions than currently done and macroprudential regulation
should be gradually extended beyond the banking sector to prevent the
migration of systemic risks. (p. 51)

UK

IMF

United Kingdom:
2016 Article IV Consultation
Concluding Statement of
the Mission,
13 May 2016

Macroprudential policy will need to tighten later this year if housing and
mortgage markets remain buoyant. Housing and mortgage markets
decelerated somewhat between mid-2014 and mid-2015 following
macroprudential tightening. More recently, however, house price growth
rose to more than three times income growth, and the share of new
mortgages at high loan-to-income (LTI) ratios is again rising. The recent
increased activity may partly reflect a temporary rush to buy houses before
higher transaction taxes on some home purchases took effect in April.
However, if current housing and mortgage market trends persist,
further macroprudential tightening (e.g., tighter LTI or loan-to-value
limits) will be needed later this year to avoid financial stability risks that
may arise from excessive household indebtedness. The buy-to-let market
has grown rapidly in recent years. It should, like the owner-occupied market,
be subject to macroprudential measures to mitigate financial stability risks
following the now-concluded Treasury consultation on this matter. It will also
be important to continue closely monitoring potential risks in the commercial
real estate market, which saw rapid price growth during 2014-15 that has
recently paused. More generally, macroprudential policy should remain
focused on financial stability and stand ready to act where necessary. This
includes communicating the objectives and tools of the Financial Policy
Committee to a broader audience, and raising the countercyclical capital
buffer as warranted by credit and asset price conditions. Indeed, the countercyclical capital buffer may well need to be increased later this year.
Directors stressed that the buoyant housing market requires ongoing efforts
to contain macroprudential risks and address long-standing supply problems.
They welcomed macroprudential measures introduced since mid-2014, but
noted that further measures may be necessary if the reduction in high loanto-income mortgages does not continue. Directors also encouraged the
authorities to extend the Financial Policy Committee’s powers of direction to
the buy-to-let market to mirror those they currently have over the owneroccupied market. They noted that ongoing efforts to reduce housing supply
constraints, such as changes to planning processes, have improved
prospects for increasing supply but require continued attention to
implementation.

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168

Imprint

© European Systemic Risk Board, 2016
Postal address
Telephone
Website

60640 Frankfurt am Main, Germany
+49 69 1344 0
www.esrb.europa.eu

All rights reserved. Reproduction for educational and non-commercial purposes is permitted provided that the
source is acknowledged.

ISBN
DOI
EU catalogue No

978-92-95081-86-4 (online)
10.2849/733467 (online)
DT-05-16-023-EN-N (online)