FINANCE AND HOUSING IN CENTRAL AND EASTERN EUROPE:
A DEMAND-SIDE APPROACH
Liviu Voinea, Deputy Governor, National Bank of Romania
Finance and Housing Panel, Bruegel Annual Meetings 2017
 Report on residential real estate and financial
In 2015, ESRB published the
stability in EU. In November 2016, a detailed assessment of countries with high
vulnerabilities followed.

AT, BE, DK, FI, LU, NL, SE, UK were identified as having medium term
vulnerabilities on the Residential Real Estate (RRE) market. No CEE country was
singled out.
 is based on the concept of "stretch", applied to households,
The ESRB methodology
collateral, and banks.
 vulnerabilities related to borrowers'
Household stretch refers to indebtedness and
ability to repay debt, as well as their capacity to maintain their consumption pattern.
Main indicators: household debt % GDP, financial assets to debt, debt service to
income.
 Collateral stretch refers to vulnerabilities relating to the property market. Main
indicators: residential price index, house price to income.

Banking stretch refers to vulnerabilities related to direct losses by banks and due to
loans'
their RRE exposures. Main indicators: loans for house purchases, growth rate
and trend.

The report finds that the structural features of the RRE markets can be grouped into
demand-side, supply-side and institutional factors. The demand side factors include:
household income, credit availability and interest rates, home ownership rates,
demographic factors. On the supply side: residential investment, housing
construction and construction costs. Institutional factors: housing taxes and
subsidies, mortgage contract features, foreclosure and insolvency procedures.

However, the report and the subsequent analysis are restricted in the definition of
structural features, in particular on the demand-side.

Financial stability is seen in the narrow sense of households being able to repay
loans, and banks being exposed to the risk of non-performing loans, mainly because
of sharp changes in the house prices. Much emphasis is put on the flow and on
trends, and little attention is being paid to the stock.
 I would like to focus on these structural features at households' level, which
eventually influence not only the RRE markets but also pose risks to financial
stability in a broader sense. The discussion is particularly timely, as residential real
estate prices have resumed an upward cycle in the last three years in all EU
countries except Greece and Cyprus.

Ex-communist countries in CEE have high ownership rates (mostly as a result of a
policy in the early 90's to sell the state's houses at affordable prices in the urban
areas, as well as due to their large share of rural population). (Figure 1).

They also have low households debt to GDP ratios and low household mortgage
debt to income ratio (Figure 2 and 3). However, these countries started from a very
low debt level (practically zero), and they witnessed only one major boom and bust
cycle of RRE prices in recent history.
 These combined features seem to spare them of RRE vulnerabilities. But the devil is
in details...meaning the structural features of households in CEE.

My point is that the analysis would benefit from having a broader perspective. We
should look beyond the household stretch to household strain, which encompasses
more structural factors.

I would refer to two dimensions of the household strain: quality of living and
inequality of income, savings, and access to credit.
 1. Quality of living:
-
- overcrowding CEE countries have the highest concentration of dependent
children, and the lowest number of rooms per person (Figure 4 and 5);
-
- poor living conditions CEE countries have the largest share of population
living in poor conditions (Figure 6);
-
- high risk of poverty or social exclusion (Figure 7) despite having high
ownership rates, CEE countries have high shares of people at risk of poverty or
social exclusion (slightly declining after EU integration);
- To partially compensate for the low quality of living, and given the social
pressure of a high ownership rate, property taxes are relatively low in CEE
countries (Figure 8);
- Low quality of living creates pressure for new housing, despite financial
difficulties to service new loans. It also creates pressure for migration, with long-
term implications for financial stability.

2. Inequality:
- Income inequality: Romania, Bulgaria and Czech Republic have the highest Gini
coefficient in the EU (Figure 9);
- Housing cost overburden: If we adjust for rent-related costs (as CEE countries
have high ownership), many CEE countries are on top.
Data on Romania:
- Housing cost overburden is very high for the first quintile, and above EU
average for up to the fourth quintile (Figure 10);
- Savings behavior: there is a strong asymmetry in the deposits' distribution (83%
of depositors have 6.6% of total deposits, while 2.7% depositors have 60% of
total deposits) (Figure 11);
Access to mortgages: skewed distribution of access to mortgages (Figure 12);
-
less than 1% of the 1st quintile, less than 2% of the 2nd and 3rd quintile. Even in
the top quintile the access to mortgage is 12%. Aggravating factors: high share of
mortgages in foreign currency (more than 2/3 before the crisis) and at variable
rates (more than 90%);
Inequality data show that a large part of the population cannot afford to buy a
-
new house in the absence of a stock of savings and that at least the first two
quintiles of households struggle with the living costs in the houses they currently
own;
Because of the lack of access to bank finance, some low to middle income
-
households resort to loans from financial institutions (NBFI), which
non-bank
have very high interest rates on very short maturities. This behavior leads to
further exclusion from financial services, because of very high debt
bank-related
servicing costs for the NBFI loans.
- Inequality matters also for the transmission of monetary policy to the economy.
For example: marginal propensity to consume, which determine household
responses to a change in interest rates, varies with income. Household access to
banks or financial markets which is typically limited for low- income households
defines who will be directly and indirectly affected by changes in interest rates,
and thus who will react more strongly to monetary policy impulses. More
generally, household response to changes in monetary conditions depends on
each household's income and indebtedness profile; that is, on their disposable
income profile. All these variables indicate that two different income
distributions can potentially induce many different impacts on the economy for
the same monetary policy1.

Access to credit has improved after the crisis, mainly due to lower interest rates
(Figure 13), income growth (in particular for low-middle income households) and
"First House" program
the introduction of a state-guaranteed (Figure 14) (which
mainly compensated for the lack of savings by allowing for a very low advance
"First House" program was changed to allow only local currency
payment). When
guarantees, the share of local currency mortgages skyrocketed (Figure 15), reducing
the vulnerability of foreign exchange evolution, but increasing the risk of a future
interest rate shock on low-middle income households.

National Bank of Romania introduced a series of macroprudential measures starting
from 2004 (Figure 16). Yet, macroprudential rules put in place to foster financial
stability can affect households unequally. For example, relaxing or tightening access
to mortgages through caps on debt-to-value ratios may affect the distribution of
household wealth.

Monetary and macroprudential policies alone cannot address the imbalances in the
RRE markets. Policies are needed to address the structural strains in the demand
side (at household level), while structural reforms are still needed on the supply side
as well.
Figure 1. Home ownership
percent
100
90
80
70
60
50
40
30
20
10
0
RO LT SK HU BG PL LV EE CZ ES SI PT CY FI IT BE IE SE NL UK FR DK AT DE
Source: ESRB Report on Vulnerabilities in the EU residential real estate sector - 2016
Figure 2. Household gross Figure 3. Household mortgage
debt-to-income ratio debt-to-income ratio
Source: ESRB Report on residential real estate and financial stability in the EU, 2015
Figure 4. Overcrowding - Households with dependent
children
RO
70
HU
BG
LV
PL
60
SK
%
50
IT
LT
40
CZ
30
AT
EE
overcrowding
20 PT
SI
SE
UK
DE
ES
FI
DK
10
IE
NL
BE
FR
CY
0
50 55 60 65 70 75 80 85 90 95 100
homeownership %
Source: Eurostat
Figure 5. Average no. of rooms per person
No. of rooms
2.5
2.0
1.5
1.0
0.5
0.0
BE IE LU UK MT DK ES FR CY FI DE SE NL AT EE PT CZ LT SI IT BG EL LV HU SK HR PL RO
Figure 6. Population living in poor conditions
percent
30
25
Total population having neither a bath, nor a
20
shower, nor indoor flushing toilet in their
household - 2015
15
10
5
0
RO LV BG LT EE HU PL HR PT CY SK DK EL UK FR AT SI FI BE CZ ES IE IT LU MT NL
Source: Eurostat
Figure 7. People at risk of poverty or social exclusion,
% total population
percent
Bulgaria
70
Czech
60
Republic
Hungary
50
40
30
20
10
0
Figure 8. Property taxes
100
RO
95
LT
HR SK
90
HU
BG
85
%
PL
EE LV
80
ES
CZ
MT
SI
EL
75
CY
FI
LU PT IT
BE
70
SE
IE
ownership NL UK
65
FR
DK
60
home
AT
55
DE
50
45
40
0.0 0.3 0.5 0.8 1.0 1.3 1.5 1.8 2.0 2.3 2.5 2.8 3.0 3.3 3.5
taxes on immovable property % of GDP
Source: Eurostat, ESRB Report
Figure 9. Gini coefficient and GDP per capita, 2015
GDP (current prices, PPS per capita)
35000
Euro area 19
30000
Czech Republic
25000
20000
Poland
Hungary
Romania
15000
Bulgaria
10000
5000
0
25 27 29 31 33 35 37 39
GINI coefficient
Source: Eurostat
Figure 10. Housing cost overburden rate - Romania
percent
60
1st
47%
50
44.9%
40
30 24%
20
10
0
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
1st Q 2nd Q 3rd Q 4th Q 5th Q
Note: percent of population with costs more than 40 % of disposable income
Costs include rental or mortgage interest payments , cost of utilities such as water,
Source: Eurostat
Figure 11. Savings behavior in Romania - 2016
percent
100
90
82.7
80
70
60
50
40 34
25.9
30
19.1
14.4
20
11.6
6.6
10
2.9
2.5
0.3
0
EUR 0-2,200 EUR 2,200-11,000 EUR 11,000- EUR 22,000- >EUR 100,000
22,000 100,000
% in total number of depositors % in total deposits
Source: BDGF
Figure 12. Access to mortgage loans
percent
14
12.3
12
10
8
6
4.0
4
2.0
1.5
2
0.9
0
1st q. 2nd q. 3rd q. 4th q. 5th q.
Note: Share of households with mortgage loans in total households, by income quintiles
Source: Ministry of Finance, Central Credit Registry, Credit Bureau
Figure 13. Access to credit
percent
24
22
20
18
16
14
12
10
8
6420
Jul-10 Jul-15
Jan-08 Jan-13
Jun-08 Apr-09 Oct-11 Jun-13 Apr-14 Oct-16
Sep-09 Feb-10 Dec-10 Sep-14 Feb-15 Dec-15
Aug-07 Nov-08 Aug-12 Nov-13
Mar-07 Mar-12 Mar-17
May-11 May-16
Interest rate of mortgage loans, RON (%) Interest rate for new mortgage loans, RON (%)
ROBOR 3 M price to income
Source: Eurostat, NBR, Credit Bureau
Figure 14. Mortgage credit and Figure 15. Share of local
the gross savings rate currency mortgages
percent percent
percent
100
16 30
14
25
75
12
20
10
8 15 50
6
10
4 25
5
2
0 0
0
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
iun.-09 iun.-12 iun.-15
sep.-08 sep.-11 sep.-14
dec.-10 dec.-13 dec.-16
mar.-10 mar.-13 mar.-16
Mortgage credit (%GDP)
Share of outstanding RON mortgage-backed
"First house" (%GDP)
credit (%)
Mortgage credit other than "First House" (%GDP)
Share of new RON mortgage-backed credit
Gross saving (%GDP) (rhs)
(%)
Source: NBR, FNGCIMM, World Bank Source: NBR, Credit Bureau
Figure 16. Macroprudential measures
August 2008:
February 2004:
December 2012:
requirements
DSTI caps (30% for
extending the
regarding the DSTI
consumer loans and
October 2006: measures to
caps should be set
35% for mortgage loans)
nonfinancial
extending the
taking into account
and LTV cap (75%)
companies lending
prudential measures
interest rate risk and
to NBFIs
FX risk
August 2005:
January 2007:
January 2016:
October 2011:
Maximum total
DSTI limit at
Higher risk-weight
LTV caps (60% - 85%)
- CCoB buffer of
40%
(100%) for commercial
and stress test
0.625% -> gradual
real-estate
parameters for DSTI
increases in equal steps
caps
March 2007:
until 2019
- O-SII buffer of 1% for
self-regulation regime
systemically important
(banks establish DSTI
banks
and LTV maximum
- CCyB buffer of 0%
levels in their internal
norms)
Source: NBR