About this dashboard
What we do
Who we are
About the HFCS
About the OeNB Euro Survey
How to contact us
Question
How vulnerable are households in Central, Eastern and Southeastern Europe?
Main definitions
Income (HFCS) = combined annual income of all members of a household (gross)
Income (OeNB Euro Survey) = combined annual income of all members of a household (net)
Gross wealth = real assets + financial assets
Vulnerability definitions
Debt-service-to-income (DSTI) ratio (HFCS) = the sum of monthly debt service divided by total household income (gross per month).
DSTI ratio (OeNB Euro Survey) = monthly loan instalment payments (interest and principal payments) divided by total household income (net per month).
Subjective vulnerability = indebted households whose expenditures exceeded their income in the last 12 months.
Negative net wealth = households holding more debt than gross wealth. The respective difference between debt and gross wealth is referred to as uncovered debt.
Loss given default (LGD) = the share of uncovered debt that households with negative net wealth and a DSTI ratio greater than or equal to 0.4 hold in relation to the total amount of debt the country owes.
Subjective LGD = the share of uncovered debt that households with negative net wealth which also left bills unpaid hold in relation to the total amount of debt the country owes.
Main background facts for the CESEE region
For detailed information on the methodology, please refer for the Austrian HFCS to the methodological notes and the first results and for the Eurosystem HFCS to the methodological report and the results report.
For detailed information on the OeNB Euro survey, please refer to the OeNB website for technical details and main results.
Source: Eurosystem HFCS 2017, OeNB Euro Survey 2018-2019.
If you hover over the countries, you will see the share of households with a DSTI ratio greater than or equal to 0.4 and the share of indebted households whose expenditures are higher than their income.
Source: Eurosystem HFCS 2017, OeNB Euro Survey 2018-2019.
The chart shows the share of households which own their main residence for several countries. The size of the dots indicates the average number of household members.
Homeownership is much more common in CESEE than in Austria, with the share of owners coming to over 90% in some CESEE countries. In Austria, by contrast, the share of households owning their main residence stands at below 50%.
Moreover, the average household size is typically larger in CESEE than in Austria. In Austria, the average household size is about 2.1, while Macedonia, for example, has a much larger household size averaging 4 persons per household.
Source: OeNB.
The chart shows the exposure of Austrian banks to several economies in CESEE. Austrian banks’ exposure is measured by the ultimate risk of the domestically controlled banks.
You can see that from end-2017 to end-2019, Austrian banks’ exposure increased in almost every country under review.
Austrian banks are particularly active in the Czech Republic, followed by Slovakia. In the Baltics, they are relatively inactive.
Source: Eurosystem HFCS 2017.
The chart shows how indebted households in different countries reacted if their expenditures exceeded their income in the last 12 months. The households in the sample could give multiple answers. If you hover over the chart, the respective answer will appear.
The highest share of indebted households that stated that they did not pay their bills was observed for Hungary, followed by Latvia and Lithuania. If these households have negative net wealth as well, they will be of interest for subjective LGDs.
Furthermore, we observed differences between countries with regard to how households react to financial shortages. In Poland, for instance, getting into new debt is more common than in other countries, whereas in Croatia, credit cards are a common tool for financing.
Selling assets is a rather uncommon reaction to shortages, households prefer to ask friends for help or to use savings. The latter is especially true for Austria and Slovakia.
Source: Eurosystem HFCS 2017.
The chart shows (subjective) LGDs for several countries. If you hover the dots, the respective labels and values will appear.
LGDs based on the subjective definition of vulnerability are in red. The legend shows LGD-size (size of the dots) for both LGD types, as opposed to the share of vulnerable households with negative net wealth which is shown on the x-axis.
You can see that subjective LGDs are lower (smaller dots) than nonsubjective LGDs in all selected countries.
The highest nonsubjective LGDs were observed for Slovenia, the highest subjective LGDs for Hungary.
For the LGD definition see the question tab.
Source: Eurosystem HFCS 2017.
The chart shows the share of indebted households with a DSTI ratio greater than or equal to 0.4 for five income shock scenarios ranging from 10% to 50%.
The share of vulnerable households increases in a nonlinear way as a consequence of the assumed shocks to income.