OeNB Report 2023/2: Eurosystem Household Finance and Consumption Survey 2021: first results for Austria

Pirmin Fessler, Peter Lindner, Martin Schürz ¹

This report presents results from the fourth wave of the Eurosystem Household Finance and Consumption Survey in Austria. After briefly outlining wave-specific issues due to the fieldwork done during times of COVID-19, we report on the state of Austrian households’ balance sheets with a focus on portfolio composition and socioeconomic characteristics across the joint distribution of wealth and income. We further examine the state of households’ saving behavior as well as their housing situation and conclude with a section on the variation of main aggregate statistics across time as developed in the joint new framework of the Eurosystem distributional wealth accounts. While, overall, the distribution of assets and liabilities among Austrian households has remained rather stable, we find the distribution of wealth has been somewhat compressed in the upper half. Also, housing and debt is increasingly concentrated in the upper half of the net wealth distribution.

The main goal of the Eurosystem Household Finance and Consumption Survey (HFCS) is to generate data on the financial situation of households and specifically households’ balance sheets (see ECB, 2023a and 2023b). The main findings about Austrian households’ assets and liabilities show very stable patterns for the HFCS waves of 2010, 2014, 2017 as well as the current 2021 wave across the distribution of (net) wealth and income. A household can be a person living alone, or a group of people who live together in the same private dwelling and share expenditures, including the joint provision of the essentials of living. The target population excludes households or individuals in institutions, i.e. hospitals, nursing homes, old persons’ homes, student residences, boarding schools, convents, prisons barracks and the like. The HFCS is the only survey and data source in Austria allowing for a comprehensive analysis of the assets and liabilities of the full household population. The main aggregates are real and financial assets as well as debt. Gross wealth is the sum of real assets and financial assets; net wealth is gross wealth minus debt. ²

With regard to the main use of the HFCS for the Eurosystem, the HFCS has become an increasingly important tool to calibrate models for monetary policy that take into account the heterogeneity of households, especially with regard to savings. Regarding financial stability, the HFCS is a key source for assessing household vulnerability.

The HFCS is especially important in Austria as there is no comprehensive credit register for natural persons. That means that a large part of debt held by households can only be analyzed based on the HFCS. Furthermore, the HFCS is the main data source for the newly developed distributional wealth accounts (DWA) of the Eurosystem, which will complement national accounts information and enrich it with distributional information. For the methodological background of the current wave of the HFCS, see our accompanying methodological report (Albacete et al., 2023) and the HFCS website ( www.hfcs.at ). Note that the ECB will soon publish a report based on the full euro area HFCS wave carried out in 2021 ³ , including many statistics for the euro area (ECB, 2023a) as well as a methodological report (ECB, 2023b). The full data for all countries and waves, including the 2021 HFCS for Austria, can be requested from the ECB for research purposes (https://www.ecb.europa.eu/stats/ecb_surveys/hfcs/html/index.en.html). For a comparison to the country economically (and institutionally) most closely related to Austria, we recommend the HFCS report recently published by the Deutsche Bundesbank (Deutsche Bundesbank, 2023): Vermögen und Finanzen privater Haushalte in Deutschland: Ergebnisse der Vermögensbefragung 2021 (bundesbank.de) .

The most important findings of the HFCS Austria can be summarized in six conclusions:

Few households hold debt in Austria (29.9%). Only 13.9% hold collateralized debt while about 17.4% hold uncollateralized debt. Collateralized debt is mostly held by households in the upper half of the net wealth distribution. Thus, potential risks to financial stability stemming from household indebtedness are relatively low in Austria compared to other euro area countries.
Austrian households have financial portfolio profiles with very low risk. Few households hold assets that are typically classified as risky. Only 12.3% of households hold mutual funds, only 6.1% hold stocks and only 2.5% hold bonds. Once households hold risky assets, these account for about 40% of their financial portfolio. This share is rather stable across the net wealth distribution.
Roughly half of Austrian households are homeowners (47.6%). Almost all of them are found in the upper half of the net wealth distribution, while the lower half of the net wealth distribution consists predominantly of households renting their homes. Only Germany has a higher share of renters in the euro area.
As in all euro area countries, the net wealth distribution in Austria is much more unequal than the distribution of income.
The net wealth distribution in Austria (and Germany) is very unequal in comparison to other countries. This is partly due to institutional differences compared to other euro area countries, related to e.g. the real estate market and the welfare state (see also box 1 on augmented wealth).
Analyzing the wealth concentration cannot be done with the HFCS data alone. That is one reason why the ECB will soon provide distributional wealth accounts (see section 5; see Kennickell et al., 2022).
Direct business ownership as well as income from renting out real estate is concentrated among the top 10% of the net wealth distribution.

The remainder of this report is structured as follows: In section 1, we discuss COVID-19-specific caveats affecting the fourth wave. Section 2 covers the main aim for the Eurosystem, i.e. gathering data on households’ balance sheets (see also box 1). We start with an assessment of the subjective wealth position in subsection 2.1, characterize the distributions of real assets, financial assets, debt and net wealth in subsection 2.2, examine extensive and intensive margins of portfolios in subsection 2.3 and deliver socioeconomic information along wealth-income profiles in subsection 2.4. The subsequent sections include special topics: Section 3 employs the data to investigate households’ saving behavior and risky asset participation, section 4 deals with the choice between homeownership and renting as well as affordability and section 5 with a comparison across all four waves as well as the new Eurosystem distributional wealth accounts. In section 6, we conclude.

Note that while this report is rather concise, we also provide a large and growing amount of additional multimedia content which is targeted at different audiences such as the general public, journalists, analysts looking for aggregated statistics (see also annex 2 as well as the Standard Output tables on our web page) and scientists who want to work with the data themselves. All the material will be accessible on the accompanying web page of this report.

German Version

https://www.hfcs.at/ergebnisse-tabellen/hfcs-2021.html

English Version

https://www.hfcs.at/en/results-tables/hfcs-2021.html

1 COVID-19-specific caveats

In the fourth wave we had several problems due to the specific situation created by the COVID-19 pandemic. The preparations for the field period had been almost completed once the COVID-19 outbreak reached Austria. Initially, the field period had been scheduled for spring to autumn 2020. We delayed interviewing by more than one year because the pandemic made personal interviews impossible. During this time, the questionnaire was adapted to include an internationally agreed set of questions concerning the impact of COVID-19. The original gross sample of households invited to participate was kept unchanged, but interviewer training had to be reorganized and conducted in digital meetings to reduce health risks. The field period started in May 2021 and lasted until February 2022. A sizable number of interviewers refused to conduct personal interviews, and a lower number of interviewers and an increased reluctance of respondents to participate in this voluntary survey led to a lower response rate. Convincing households to participate in the fourth wave was an extraordinary challenge. It seems, however, that those households that did answer were more committed, as item-nonresponse rates decreased. On the other hand, households at the top end of the distribution that had already been hard to reach in previous waves, are even more scarcely represented in the sample than in the past waves.

Due to these problems arising from a field period amid a pandemic, many technical processes in post-fieldwork production also had to be adjusted, most notably editing and weighting schemes. Furthermore, fewer observations made multiple imputations more difficult as well. We document the COVID-19-related methodological problems and resulting caveats in Albacete et al. (2023).

2 Balance sheets

This main section of the report lays out results on households’ balance sheets. We start with respondents’ subjective assessment of their wealth position and then move on to real as well as financial assets and debt.

2.1 Subjective wealth position

Perceptions and preferences are crucial for understanding individual economic behavior (see Schürz, 2019). Therefore, we start our analysis with the perspective of the households themselves. Chart 1 shows the answers to a question ⁴ on households’ self-assessment regarding their own position in the wealth distribution in waves 3 and 4. Respondents misclassify their household with a strong bias toward the middle of the distribution. Hardly any wealthy respondents believe that their own households belong to the upper quintile of the wealth distribution.

Furthermore, also at the very low end of the distribution, we find relatively few households assessing their position in the wealth distribution correctly.

2.2 Characteristics of wealth distribution

As a next step, we present the main components of net wealth in the charts below. Charts 2 through 5 show the distribution of household real assets, financial assets, debt and net wealth. The calculation covers all households that do not own a particular wealth component with an asset value of zero. We select an interval from the 5th to the 95th percentile for the chart to avoid coverage problems at the upper and lower tails of the distribution.

Zero ownership of real assets is reported by a fairly large number of households (14.3%). To a certain extent, this may reflect the underreporting of less valuable items. Not until the middle of the distribution do real asset holdings begin to increase markedly. Below the middle of the distribution, vehicles are the dominant type of real asset. The 47.6% of households that own their main residence can be found almost entirely in the upper half of the net wealth distribution (see also table 4).

The conditional mean of real assets is calculated based on households with real assets. It comes to about EUR 305,000. Real asset holdings rise sharply in the middle and then evenly up to the 90th percentile (see chart 2), reflecting widespread owner-occupied housing starting in the upper middle and relatively evenly distributed current values of households’ main residences (see Fessler and Schürz, 2017a). Real asset values rise noticeably at the top, especially the values above the 95th percentile. In this range of the distribution, other real estate property and investments in self-employment businesses begin to play a key role in addition to main residences.

Chart 3 shows the distribution of financial assets. Only very few households (0.1%) own no financial assets at all. For this reason, the conditional and unconditional means are nearly identical at around EUR 48,000. Both these values are far higher than the (unconditional) median at some EUR 18,000, which indicates a pronounced positive skewness of the distribution. The financial wealth of roughly three-quarters of all households falls short of the mean. However, underreporting is especially high for financial wealth in general, and the degree of understatement is most likely to be very large in the upper range of the distribution (see also Andreasch and Lindner, 2016; Vermeulen, 2016).

Chart 4 shows the distribution of debt from the 5th to the 95th percentile. 71.1% of Austrian households do not have any debt. The conditional mean of debt comes to approximately EUR 54,000. Small liabilities are primarily unsecured loans or, in a few instances, secured loans that have been almost paid off. Large debt amounts mainly reflect mortgage loans at various stages of repayment. Note, however, that in recent years especially loans for additional real estate beyond owner-occupied housing have increased. The very affluent are increasingly accumulating real estate wealth, while the share of owner-occupiers remained roughly constant at about half of the household population for the last 20 years. The expansion in real estate wealth and accompanied debt is therefore not driven by an expansion in homeownership rates but by an expansion in real estate wealth at the intensive margin.

Chart 5 shows the distribution of net wealth for the third and the fourth wave. In 2021, 3.6% of households had negative (3.3%) or no net wealth (0.03%). At about EUR 293,000, the mean is considerably higher than the median of around EUR 128,000. Net wealth of over EUR 1 million is observed only in the top 5% of households. Compared to 2017, the distribution is compressed in the upper half as values increased by similar absolute amounts between P50 and P85 (by EUR 50,000 to EUR 100,000) and between P85 and P95 (by up to EUR 200,000). Relatively, that means larger increases for the P50–P85, which in turn indicates a reduction in measured inequality in the upper half of the wealth distribution. This partly reflects increases in real estate wealth in the upper half as well as increased savings of more affluent households in recent years.

2.3 Portfolio composition

The components of net wealth can be analyzed in detail at the level of their subcomponents. First, we determine household participation, i.e. we establish how many households have a specific asset or a liability. Second, we compute the conditional median and the conditional mean for the households reporting this component. The median divides a distribution into two halves. The arithmetic mean is the value that would result for every household owning such an item if the entire volume of wealth were equally distributed. The median is a statistically robust measure while the mean is not. The mean-to-median ratio is computed as an indicator of the skewness of the distribution within the wealth component under review. ⁵

Table 1 provides an overview of the key components of net wealth. All wealth components have a positively skewed distribution as the mean is higher than the median. Some 47.6% of households own their main residence at least partially. In this component of wealth, the median value of the main residence of owner households is around EUR 280,000, and the average value of the main residence of owner households amounts to about EUR 372,000. Main residence ownership represents the most important asset in terms of volume for the owners. About 17% of households own other valuables, such as gold, works of art, jewelry, collections, etc. With a median value around EUR 5,000, the values in this wealth component are rather low. About 10.9% of households own real estate assets other than their main residence, ⁶ above all houses, apartments and undeveloped land. With a conditional mean of some EUR 350,000, the mean of other real estate property is almost as high as that of the main residences, while the median is considerably lower. Around 5.4% of households have investments in self-employment businesses (including agricultural businesses), i.e. businesses in which at least one household member is actively involved. Both the median (around EUR 78,000) and the mean (around EUR 579,000) of this component of wealth are comparatively high. The slightly decreasing extensive and intensive margins of this item, which is mostly held at the top of the net wealth distribution points toward a somewhat lower coverage at the top of the distribution.

Savings accounts, which in the HFCS Austria include savings plans with building and loan associations and life insurance contracts, are by far the most common savings variant. About 83% of households have at least one savings account, 34% have at least one savings plan with a building and loan association, and 35% have at least one life insurance contract. The median of savings accounts comes to around EUR 16,000 and the mean to some EUR 32,000. Roughly, 7% of households have made voluntary private pension provisions. This component of wealth contains state-sponsored retirement provision plans and other dedicated private savings plans for retirement. The median runs to roughly EUR 11,000 and the mean to about EUR 35,000. 12.3% of households have invested in mutual funds. The median of this component of wealth is around EUR 21,000 and the mean value about EUR 56,000. About 8% of households state that they have lent money to others. Stocks are held by 6% of households, bonds by around 3%. The medians run to about EUR 15,000 (stocks) and around EUR 18,000 (bonds), which compares with corresponding means of about 40,000 (stocks) and around EUR 94,000 (bonds). The residual measure “other financial assets,” for which about 2.9% of households reported values, comprises financial assets that are not recorded in any other category. This includes, for instance, silent partnerships, deferred compensation, trademark rights and accounts managed by trustees.

Table 1: Components of net wealth
		Participation	Conditional median	Conditional mean	Mean-to- median ratio
		%	EUR thousand
Real assets	Vehicles	78.1	10.0	16.4	1.6
	Main residence	47.6	280.8	372.1	1.3
	Other valuables	17.1	5.0	11.8	2.4
	Other real estate property	10.9	179.8	350.3	1.9
	Investment in self-employment business (incl. farms)	5.4	77.6	579.2	7.5
Financial assets	Sight accounts	99.7	1.7	5.1	3.1
	Savings accounts	83.0	16.3	31.5	1.9
	Savings plans with building and loan associations	34.3	4.0	5.9	1.5
	Life insurance contracts	35.1	12.4	20.2	1.6
	Voluntary private pension plans	6.7	10.8	34.8	3.2
	Mutual funds	12.3	20.7	56.2	2.7
	Money owed to households	7.6	3.5	11.4	3.2
	Stocks	6.1	14.8	40.3	2.7
	Bonds	2.5	17.6	93.9	5.3
	Other financial assets	2.9	14.9	50.5	3.4
Debt	Collateralized debt	13.9	53.0	96.1	1.8
	Main residence	12.8	51.0	92.6	1.8
	Other real estate property	1.3	65.0	111.2	1.7
	Uncollateralized debt	17.4	2.7	14.2	5.2
	Overdrafts	9.2	1.3	2.1	1.6
	Uncollateralized loans	8.8	7.2	25.4	3.5
	Loans from family and friends	2.9	3.1	15.3	4.9
	Outstanding balance on credit cards	3.0	0.7	0.9	1.3
Source: HFCS Austria 2021, OeNB.

12.8% of households have debt for which they use their home as collateral. The difference between the median of about EUR 51,000 and the mean of around EUR 93,000 reflects variations across households both in the original amounts borrowed and the repayment of loans over time. Only 1.3% of households have taken out loans using other real estate property as collateral; however, the value of these loans is higher than that of loans secured by the main residence as collateral. An increasing share of collateralized debt is used for real estate other than the main residence. While the conditional mean and median decreased for the stock of loans using the main residence as collateral, those using other real estate property sharply increased since the last wave in 2017.

17.4% of households have uncollateralized debt. The distribution is significantly more skewed than that of collateralized debt. Moreover, 8.8% of households have overdrawn at least one of their sight accounts by a median of about EUR 1,000; the average value of this component is EUR 2,100. Other uncollateralized loans, amounting to an average of about EUR 25,000, represent the largest component of uncollateralized debt. Outstanding credit card balances play a minor role in Austria, with only 3% of households holding such debt and with the median and the mean coming to a comparatively low level of around EUR 700 and EUR 900, respectively. Austrians generally continue to use credit cards rather like debit cards, settling their bills in full every month.

2.4 Equivalized income, portfolio choice and socioeconomic characterization across wealth-income clusters

The households in the lower half of the net wealth distribution hold only small amounts of wealth; if any, they tend to have financial assets rather than real assets. An additional 40%, between the median and P90, own their main residence and little else. Some 10% have net wealth totaling more than EUR 700,000 that – besides household main residences – consists mainly of other real estate property and investments in self-employment businesses.

Income is important to assess the financial situation of households, as it is the base for their day-to-day consumption and for housing, in the case of renters, as well as their saving capacities. Next to intergenerational transfers, saving capacities are the second major source of wealth accumulation. Therefore, we describe the socioeconomic patterns along the resulting wealth-income combinations of the lower half, upper middle and top 10% of the net wealth as well as equivalized net income distributions (see Fessler and Schürz, 2022; and Fessler and Schürz, 2023).

Table 2 shows the prevalence of households within equivalized households’ income and net wealth groups. Income and wealth are positively correlated. 30.9% (out of potentially 50%) of households belong to the lower half of the equivalized net household income distribution as well as the lower half of the net wealth distribution at the same time. 18.7% (out of potentially 40%) belong to the upper middle (between P50 and P90) and 3.4% (out of potentially 10%) to the top 10% of both distributions. There are also a few households (2.4%) that belong to the lower-half income group but top 10% wealth group and even fewer (1.8%) to the lower-half net wealth group but top 10% income group.

Table 2: Income and wealth
	Net wealth
Equivalized net household income	Lower half (<P50)	Upper middle (P50-P90)	Top 10 (>P90)
	Share in population in %
Lower half (<P50)	30.9	16.5	2.4
Upper middle (P50-P90)	17.3	18.7	4.2
Top 10 (>P90)	1.8	4.8	3.4
Source: HFCS Austria 2021, OeNB.

Table 3 presents different sources of wealth accumulation for these groups. The 30.9% of households located in the lower half of the equivalized household net income distribution and the lower half of the net wealth distribution have the lowest mean income. ⁷ They have a lower saving rate, and a much lower share of them has already inherited. As only few of them are owner-occupiers, most of them must pay a large share of their income for renting. The share of business owners and the share of households with rental income in this group is particularly low. This is in sharp contrast to the six groups in the upper half of the wealth distribution, where about 90% are owner-occupiers as opposed to below 10% in the lower half. Owning one’s home has a great advantage as income from imputed rent is not taxed and potential payments for housing in the form of debt service represent savings. Renters on the other hand pay value-added tax on their rent, and rents are rising with the consumer price index. Also, the share of households who have already inherited is about 50% in the three groups with upper-middle wealth and between 67.7% and 83.2% in the top 10% wealth groups. The share of business owners and households with rental income rises particularly strongly only for the three groups within the top 10% of wealth. Statistics for the smaller groups should be interpreted carefully and only as indications of differences in relation to the others as they are based on small numbers of observations.

Table 3: Sources of wealth
	Share in population	Monthly equivalized net income	Saving rate	Share of heirs	Share of owner- occupiers	Share of business owners	Share with rental income from real estate
	%	EUR thousand	% of net income	Share in population in %
Wealth<P50, income<P50	30.9	1.3	9.6	24.2	4.4	1.2	0.4
Wealth<P50, P50<income<P90	17.3	2.1	13.2	25.5	7.2	2.2	0.9
Wealth<P50, P90<income	1.8	3.3	11.6	35.6	2.5	4.3	0.0
P50<Wealth<P90, income<P50	16.5	1.4	18.0	50.2	93.4	5.0	4.1
P50<Wealth<P90, P50<income<P90	18.7	2.2	18.0	49.7	87.6	5.0	4.7
P50<Wealth<90, P90<income	4.8	3.4	20.8	51.5	80.5	9.4	8.3
P90<Wealth, income<P50	2.4	1.4	25.3	67.7	94.4	31.0	26.0
P90<Wealth, P50<income<P90	4.2	2.3	24.2	83.2	94.8	22.4	23.6
P90<Wealth, P90<income	3.4	3.8	28.4	75.6	89.5	18.7	14.9
Source: HFCS Austria 2021, OeNB.

Table 4 describes the average portfolio composition (unconditional values) across the different income-wealth groups. The large difference between the groups in the lower half of the wealth distribution and those in the upper middle is driven – not in a causal sense – mostly by owner-occupied housing, which is the main asset in the upper middle. Within the upper middle of the wealth distribution, real assets do not change much with increasing income. Within the top 10%, there is even a decrease in average real assets with income, which is mostly due to the large prevalence of farmers (see also table 6) with large real wealth but low income. Financial assets, on the other hand, also increase with income within the top 10%.

Table 4: Portfolio composition
	Share in population	Real assets	+ Financial assets	– Debt	= Net wealth
	%	EUR thousand
Wealth<P50, income<P50	30.9	10.6	10.9	3.9	17.5
Wealth<P50, P50<income<P90	17.3	30.0	22.9	12.5	40.4
Wealth<P50, P90<income	1.8	28.2	33.9	10.4	51.6
P50<Wealth<P90, income<P50	16.5	287.5	37.4	19.6	305.2
P50<Wealth<P90, P50<income<P90	18.7	294.0	51.4	20.7	324.7
P50<Wealth<90, P90<income	4.8	300.2	87.8	31.0	356.9
P90<Wealth, income<P50	2.4	1,880.6	101.2	12.5	1,969.3
P90<Wealth, P50<income<P90	4.2	1,143.0	173.7	26.0	1,290.7
P90<Wealth, P90<income	3.4	1,229.1	293.6	66.3	1,456.5
Source: HFCS Austria 2021, OeNB.

Table 5 shows the income composition of wealth-income groups (based on equivalized household net income). Income (based on detailed gross income measures) from work (employed, self-employed, state and private pensions, unemployment insurance and private transfers ⁸ ) is the most important income source for all groups. In absolute terms, social transfers (child benefit, student allowance, parental leave allowance, sickness benefit, care allowance, family allowance, social welfare, emergency assistance, housing allowance) decrease with income in all groups but the top 10% wealth group, where households are larger compared to the groups with lower wealth. Interestingly, the largest mean social transfers are received in the group that belongs to the top 10% of both, income and wealth. Relative to this group’s income they are less important. Income from capital (from renting out real estate, from financial assets and from business participations) is largest for wealthy households.

Table 5 : Income composition
	Share in population	Income from work	+ Social transfers	+ Income from capital	= Gross income
	%	EUR thousand
Wealth<P50, income<P50	30.9	26.9	1.5	0.1	28.5
Wealth<P50, P50<income<P90	17.3	52.4	0.8	0.2	53.4
Wealth<P50, P90<income	1.8	77.4	0.5	0.1	78.0
P50<Wealth<P90, income<P50	16.5	40.0	1.4	0.4	41.8
P50<Wealth<P90, P50<income<P90	18.7	61.2	0.8	0.3	62.3
P50<Wealth<90, P90<income	4.8	96.6	0.7	2.1	99.4
P90<Wealth, income<P50	2.4	31.2	1.5	6.0	38.7
P90<Wealth, P50<income<P90	4.2	71.4	1.3	3.6	76.3
P90<Wealth, P90<income	3.4	109.7	3.0	5.0	117.7
Source: HFCS Austria 2021, OeNB.

Table 6 presents socioeconomic characteristics of the income-wealth groups. Household size is smaller for groups with lower wealth. Single parent households are particularly prevalent in the low-income groups (if they can stay in owner-occupied housing also in the upper part of the wealth distribution). Within lower-wealth groups, more people live in cities, where in general there are more renters. But within wealth groups, the share of households located in cities rises with income. While there are no large differences in age among the financially knowledgeable persons in the households, the share of respondents with university education rises with both income and wealth. Unemployed persons are mostly found in the group located in the lower half of the wealth and income distribution. Farmers on the other hand mostly belong to the lower income groups of the top 10% wealth group.

Overall, these results show once again that it is key to assess both income and wealth to describe the financial situation of a household.

Table 6: Socioeconomic characterization
	Household characteristics				Financially knowledgeable person characteristics
	Share in population	Household size	Share of single-parent households	Share living in a city (population >20,000)	Age	Share with university degree	Share of unemployed	Share of farmers
	%	Mean	%		Mean	%
Wealth<P50, income<P50	30.9	1.8	3.8	55.9	54.0	7.9	10.0	0.2
Wealth<P50, P50<income<P90	17.3	1.9	0.2	60.3	53.3	7.6	1.9	0.3
Wealth<P50, P90<income	1.8	1.7	0.0	78.7	52.1	22.1	0.3	0.0
P50<Wealth<P90, income<P50	16.5	2.4	1.1	25.2	59.9	8.6	3.9	1.0
P50<Wealth<P90, P50<income<P90	18.7	2.3	0.3	29.1	57.9	16.2	0.2	0.7
P50<Wealth<90, P90<income	4.8	2.1	0.0	40.9	57.3	34.3	0.0	0.0
P90<Wealth, income<P50	2.4	2.4	5.0	19.6	60.4	9.4	0.6	11.8
P90<Wealth, P50<income<P90	4.2	2.4	0.0	23.5	58.6	34.9	0.9	5.0
P90<Wealth, P90<income	3.4	2.4	0.0	39.6	57.0	42.2	0.8	0.0
Source: HFCS Austria 2021, OeNB.
Note: Single parent households are defined as households with only one adult person (household member aged 18 or older) and one or more household members aged 14 or younger.

3 Saving behavior

Besides intergenerational transfers (gifts and inheritances), savings out of regular income are the major source of household wealth (see Fessler and Schürz, 2017b). While lower-income households save for vacations or the replacement of larger consumption goods (such as cars, dishwashers, washing machines or furniture) households with higher income and/or inheritances/gifts also save for down payments on owner-occupied housing. The 30.9% of households that fall in the lower half of the income and wealth distribution have average monthly savings of around EUR 180, while approximately 45% of households that pay rent save around EUR 280 per month. The medians are at EUR 100 and EUR 200, respectively. Additional support in the form of gifts or inheritances is almost a prerequisite for being able to afford owner-occupied housing.

As chart 6 shows, the saving rate (as a share of net income) increases with equivalized net income, also if variation due to education levels (four categories) as well as age (and age squared) is filtered out (see chart 6b).

Those households that accumulate wealth mostly do so in safe financial assets (see table 1) and/or at some point transfer their financial assets (as well as potential inheritances and/or gifts) into owner-occupied housing. Wealthier households hold risky assets. But even in the upper part of the distribution, the share stays below 50% for mutual funds, stocks and bonds. Once households invest in risky assets, such assets account for 40% of their financial assets (see chart 7 and Bekhtiar et al., 2019).

4 Housing

Housing is key to understanding the wealth distribution (see Fessler and Schürz, 2018a and 2023). Being an owner-occupier is strongly (positively) correlated with income (chart 8, right-hand panel) and even more so with net wealth (chart 8, left-hand panel). Some people care about bequests; others face borrowing constraints (like down payment requirements); and in general people show less than fully rational behavior ⁹ . The tax system favors homeownership vis-à-vis renting. In Austria, the correlation is especially strong. The homeownership rate is rather stable showing only a small decline in the last 20 years. Declining affordability leads to a higher correlation of homeownership with the net wealth distribution and a larger dependence on intergenerational transfers for financing the down payment necessary to buy a home. As foreign investors as well as homeowners in the upper half of the wealth distribution who invest in additional real estate are closing the gap left by the slightly lower number of owner-occupiers, this leads to a situation in which fewer owners own more as well as more expensive real estate than before.

Affordable rents as well as higher income for households in the lower half of the wealth distribution are essential ingredients for increasing their saving potential to accumulate more wealth. From a social and environmental point of view, however, fostering and particularly subsidizing homeownership and especially single-family homes is a well-documented major policy mistake (see Orsetta et al., 2019; Economist, 2020a and 2020b; Fessler and Schürz, 2018b).

5 Assets and liabilities over time and the distributional wealth accounts

One major problem of wealth surveys is the coverage of the top of the distribution as well as the underreporting by the wealthy. Still, whereas we know that the HFCS data are not a good tool for analyzing wealth concentration, the broader phenomenon of a compression in the upper half of the distribution in recent years is a robust result. Households between P50 and P90 recorded the largest relative wealth increases since the last HFCS wave, likely due to higher saving capacities and increasing real estate prices. So while the share of the upper 20% and upper half of the distribution in overall wealth hardly changed, the measured share of the top 1% fell markedly. While that might be partly due to measurement issues and coverage problems, it might also be a result of this relatively strong increase in housing wealth and savings in the upper middle as well as a decrease in the shareholder value at the top of the distribution in the recent COVID-19 pandemic.

Augmented wealth and the measurement of inequality

The definition of net wealth is based on an internationally agreed standard – based on marketable wealth (see Davies and Shorrocks, 2000; OECD, 2013) – where the assets of the household balance sheet are summed up to form gross wealth and all possible forms of liabilities are subtracted. The assets include real assets (real estate, cars, business assets and valuables) and financial assets (sight and savings accounts, assets invested in life insurances, (mutual) funds, bonds, shares, debt owed to the household, other financial assets). In particular, future entitlements of any form are not part of the definition of net wealth, since they are in general not transferable and cannot be used as collateral. For a broader definition of wealth that also includes potential future entitlements from publicly provided social benefits, the term “augmented wealth” is used in the literature. This may include pension entitlements, publicly provided health services or public housing, since these potential future entitlement can be seen as a substitute for wealth for some parts of the population (see also Fessler and Schürz, 2018a). A literature example for Austria is Knell and Koman (2020), who combine the information from the HFCS and social security register to estimate pension entitlements and add it to net wealth, leading to a substantial reduction in the measured Gini coefficient from 0.7 toward 0.5. Furthermore, there is an ongoing project to estimate the implicit valuation of the health insurance system and social housing for households. Future research could focus on the theoretical foundation of the wealth concept used.

Furthermore, survey data of the HFCS in Austria are based on repeated cross sections of the household population. This means that the standard measurement of the distribution comprises all households over their life cycle. A possibility would be to assess inequality within one age group. A household consisting of young members, who have their lifetime to accumulate wealth, might display a different wealth level than a household consisting of persons at the end of their working life. This can be measured by comparing the wealth of an age group around retirement (60–65 years); if the sample in this age group is too small, this can be realized by oversampling in a future HFCS wave. Within age cohorts, inequality is expected to be lower than inequality for the full population if the life cycle consumption hypothesis holds. Future research could shed some light on this topic.

The HFCS data do not enable us to estimate the shares at the very top precisely enough to establish statistically significant results (with regard to differences over time) given our sample size and the absence of oversampling of the very wealthy.

Table 7: Inequality measures 2010–2021
		2010		2014		2017		2021
		Gross wealth	Net wealth	Gross wealth	Net wealth	Gross wealth	Net wealth	Gross wealth	Net wealth
Inequality measures	Gini coefficient	0.73	0.76	0.71	0.73	0.71	0.73	0.68	0.69
	GE(2)	4.0	4.5	10.2	11.5	7.4	8.5	2.2	2.4
	P75/P25	22.4	24.3	27.0	28.6	21.7	21.6	20.9	21.7
	P90/median	6.2	7.1	5.4	6.0	5.7	6.3	5.2	5.5
	P90/P10	233.7	581.1	251.8	521.2	171.9	262.0	222.4	297.8
		%
Top shares	Top 1	21.7	22.9	23.9	25.4	21.4	22.6	15.3	16.3
	Top 5	45.5	47.6	41.6	43.4	41.2	43.1	36.0	37.1
	Top 10	58.8	61.1	53.5	55.5	54.2	56.4	50.3	51.5
	Top 20	74.4	76.6	70.0	72.1	70.9	72.8	68.6	69.7
	Bottom 50	3.9	2.8	4.0	3.2	4.3	3.6	4.9	4.6
Source: HFCS Austria 2010, HFCS Austria 2014, HFCS Austria 2017, HFCS Austria 2021, OeNB.
Note: The Gini coefficient may take a value greater than 1 if the data contain negative values. GE(2) is a generalized entropy index with α = 2.

Recently, the ECB developed so-called distributional wealth accounts (DWA), ¹⁰ which integrate the HFCS data and the System of National Accounts (SNA). ¹¹ Several adjustments to various parts of the household balance sheet are followed by the simulation of the top of the distribution applying a Pareto distribution and using rich lists. ¹² And finally, an alignment of aggregates with the microdata is achieved by a detailed proportional adjustment. ¹³ Once micro- and macrodata are brought in line with each other at the time of survey, all the quarters in between are interpolated and quarters after the most recent survey (so far only the first three waves of the HFCS have been integrated) are forecast.

Looking at the mean and median figures for Austria, Germany ¹⁴ and the euro area, we see that these indicators (see chart 9) have been rising in all countries over the last decade. The mean of net wealth has been increasing even more steeply than the median. Additionally, mean net wealth in Austria is generally above the international average whereas median levels in Austria and Germany are lower than for the euro area, but very close to each other. The co-movement of results for Germany and Austria over time is remarkable.

On the other hand, inequality measures have shown extraordinary stability over the last decade. The shares of net wealth held by the top 5% are particularly high in Austria in comparison to its international counterparts. Based on DWA data, Engel et al. (2022) from the ECB report a top 1% share for Austria of 40% in Q3 2022 compared to a euro area figure of some 28%. Kennickell et al. (2021) present various scenarios resulting from simulations of wealth concentration in Austria. The results of these simulations show that the top 1% of Austrian households in terms of net wealth account for a share in total household net wealth that ranges from at least 23% to more than 50%.

6 Final remarks

The public discourse based on HFCS data is mostly centered on questions of wealth inequality. Overall we find that, compared to other European countries and measured by standard inequality measures, inequality of net wealth is rather large in Austria. Inequality is also very persistent over time. The survey alone does not enable us to analyze wealth concentration at the top and, more specifically, its change over time as measures are biased and not precise enough due to issues of coverage and underreporting by the very affluent. However, the ECB’s distributional wealth accounts, which use additional assumptions to fill the gap between HFCS survey data and aggregate national accounts data, confirm the result of very persistent inequality. The extent of inequality is much higher once the raw data are adjusted using such methods. Important reasons for particularly high measured wealth inequality in Austria (and Germany) are institutional differences compared to other euro area countries, e.g. in relation to the rental market and the welfare state. Furthermore, the OeNB provides platforms for discussing the issue of so-called augmented wealth, trying to assess the role specific institutional differences play when comparing the net wealth distribution across countries (see OeNB workshop on augmented wealth: https://www.youtube.com/watch?v=PAid_yjOJQU ).

Like Germany, Austria has a comparably low rate of indebted households with a comparably large risk-bearing capacity. The main reason is that both countries have large (subsidized) rental housing markets, which allow lower-income households to rent instead of taking out large amounts of mortgage debt to buy their home (only 47.6% of households are homeowners). Only 13.9% hold mortgage debt while about 17.4% hold nonmortgage debt. Mortgage debt is mostly held by households in the upper half of the net wealth distribution.

Concerning the asset side, few households hold assets that are typically classified as risky. Only 12.3% of households hold mutual funds, only 6.1% hold stocks and only 2.5% hold bonds. In the upper middle below the top 10%, owner-occupied housing is usually the by far largest asset households hold. Direct business ownership as well as income from renting out real estate is concentrated among the top 10% of the net wealth distribution.

References

Albacete, N., P. Lindner and K. Wagner. 2023. Eurosystem Household Finance and Consumption Survey 2021: Methodological notes for Austria.

Andreasch, M. and P. Lindner. 2016. Micro- and Macrodata: a Comparison of the Household Finance and Consumption Survey with Financial Accounts in Austria. In: Journal of Official Statistics, Vol. 32, No. 1. 1–28.

Bekhtiar K., P. Fessler and P. Lindner. 2019. Risky assets in Europe and the US: risk vulnerability, risk aversion and economic environment. ECB Working Paper Series No. 2270.

Causa O., N. Woloszko and D. Leite. 2019. Housing, wealth accumulation and wealth distribution: Evidence and stylized facts. OECD Economic WP 1588.

Davies, J. and A. Shorrocks. 2000. The distribution of wealth. In: Atkinson, A.B. and F. Bourguignon (eds.). Handbook of Income Distribution, Vol. 1, Elsevier. Ch. 11. 605–675.

Deutsche Bundesbank. 2022. Distributional Wealth Accounts for households in Germany – results and use cases. Monthly Report July.

Deutsche Bundesbank. 2023. Vermögen und Finanzen privater Haushalte in Deutschland: Ergebnisse der Vermögensbefragung 2021. Monatsbericht April.

ECB. 2023a. The Household Finance and Consumption Survey: Results from the 2021 wave. Statistics Paper Series Forthcoming.

ECB. 2023b. The Household Finance and Consumption Survey: Methodological report for the 2021 wave. Statistics Paper Series Forthcoming.

Economist. 2020a. Home ownership is the West’s biggest economic-policy mistake. Home ownership is the West’s biggest economic-policy mistake (economist.com)

Economist. 2020b. Housing is at the root of many of the rich world’s problems. Housing is at the root of many of the rich world’s problems (economist.com)

Engel, J., P. G. Riera, J. Grilli and P. Sola. 2022. Developing reconciled quarterly distributional national wealth – insight into inequality and wealth structures. ECB Working Paper Series No. 2687. July.

Expert Group on Linking macro and micro data for the household sector. 2020. Understanding household wealth: linking macro and micro data to produce distributional financial accounts. ECB Statistics Paper Series No. 37.

Fessler, P. and M. Schürz. 2017a. Zur Mitte in Österreich. In: Österreichischer Sozialbericht 2015-2016. Bundesministerium für Arbeit, Soziales und Konsumentenschutz. 269–292.

Fessler, P. and M. Schürz. 2017b. Zur Verteilung der Sparquoten in Österreich. In: Monetary Policy & the Economy Q3/17. OeNB. 13–33.

Fessler, P. and M. Schürz. 2018a. Private Wealth Across European Countries: The Role of Income, Inheritance and the Welfare State. In: Journal of Human Development and Capabilities, 19:4, DOI: 10.1080/19452829.2018.1507422. 521–549.

Fessler, P. and M. Schürz. 2018b. Housing and the American Dream: Is A House Still a Home? INET Blog.

Fessler, P. and M. Schürz. 2022. Structuring the Analysis of Wealth Inequality – Using the Functions of Wealth: A Class-Based Approach. In: Measuring Distribution and Mobility of Income and Wealth, National Bureau of Economic Research.

Fessler, P. and M. Schürz. 2023. Homeownership: The key to wealth inequality? In: Schifferes, S. and S. Knowles (eds.). The Media and Inequality – 1st Edition.

Fessler, P., P. Lindner and M. Schürz. 2018. Eurosystem Household Finance and Consumption Survey 2017 for Austria. In: Monetary Policy & the Economy Q4/18. OeNB. 36–66.

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Knell, M. and R. Koman. 2015. Pension Entitlements and Net Wealth in Austria. OeNB Working Paper 238.

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Annex I

Table A1: Self-assessment by net wealth deciles
	All households	Households with incorrect self-assessment
Actual decile	Correct self-assessment	Average misestimation	Average estimated decile
	%	Deciles
1	39.2	2.2	3
2	22.6	1.3	3
3	24.0	0.9	4
4	20.3	0.4	4
5	26.2	–0.6	4
6	14.3	–1.4	5
7	13.0	–2.2	5
8	2.6	–3.1	5
9	0.1	–3.7	5
10	5.9	–4.0	6
Source: HFCS Austria 2021, OeNB.

Annex II

This annex provides additional descriptive information and offers a comprehensive overview of various topics. The additional information contained within these tables aims to offer researchers, policymakers, and other interested parties comprehensive information on topics we could not cover in the main text. We are confident, that the tables presented in this annex serve as a valuable supplement to the main text and the standard output tables available online (https://www.hfcs.at/en/results-tables/hfcs-2021.html).

It includes tables on socioeconomic characteristics, additional characteristics along the income and wealth distribution, the household main residence, mortgages and household vulnerability, variables typically used for (the calibration of) macro models, and COVID-19 related information.

1 Socioeconomic characteristics

Table A1a: Net wealth by age groups
Age	Population share	Mean	Median
	%	EUR thousand
0–24 years	2.7	41.4	7.7
25–39 years	15.1	174.5	29.7
40–59 years	37.0	352.7	170.3
60 years and over	45.2	298.9	170.5
Source: HFCS Austria 2021, OeNB.
Note: This table shows population shares as well as mean and median net wealth across age categories, with age referring to the age of the financially knowledgeable person.

Table A1b: Net wealth by education level
Education	Population share	Mean	Median
	%	EUR thousand
Compulsory education or below	14.6	141.9	22.2
Apprenticeship, vocational school	35.7	212.6	85.7
Upper secondary, school-leaving certificate	36.2	370.0	166.6
University, technical college	13.4	464.1	278.3
Source: HFCS Austria 2021, OeNB.
Note: This table shows population shares as well as mean and median net wealth across education categories, with the level of education referring to the financially knowledgeable person.

Table A1c: Net wealth by occupation status
Occupation	Population share	Mean	Median
	%	EUR thousand
Self-employed	4.1	670.9	428.1
(Skilled) blue-collar worker	11.3	185.8	36.7
White-collar worker	28.9	275.5	163.4
Civil servant	3.1	308.4	229.3
Farmer	0.9	2,122.8	927.8
Pensioner	43.1	293.7	161.3
Unemployed	4.2	83.8	6.7
Other	4.5	145.3	9.8
Source: HFCS Austria 2021, OeNB.
Note: This table shows population shares as well as mean and median net wealth across occupational categories, with the occupation status referring to the financially knowledgeable person.

Table A1d: Net wealth across the income and wealth distribution
Distribution	Population share	Wealth share	Mean	Median
	%		EUR thousand
1st gross income decile	10	5.1	149.2	5.9
2nd gross income decile	10	6.2	183.0	15.4
3rd gross income decile	10	5.3	156.3	21.1
4th gross income decile	10	7.3	213.9	47.8
5th gross income decile	10	8.7	254.6	128.4
6th gross income decile	10	10.0	292.4	164.0
7th gross income decile	10	10.3	301.1	168.9
8th gross income decile	10	10.9	318.6	206.1
9th gross income decile	10	11.2	329.0	216.6
10th gross income decile	10	25.0	733.3	465.2
1st net wealth decile	10	-0.2	-5.5	0.3
2nd net wealth decile	10	0.2	5.6	5.1
3rd net wealth decile	10	0.6	16.2	15.8
4th net wealth decile	10	1.2	36.0	35.1
5th net wealth decile	10	2.8	81.6	79.3
6th net wealth decile	10	5.9	172.5	173.0
7th net wealth decile	10	8.2	240.6	238.3
8th net wealth decile	10	11.7	341.9	340.7
9th net wealth decile	10	18.1	531.6	518.6
10th net wealth decile	10	51.5	1514.4	1048.8
Source: HFCS Austria 2021, OeNB.
Note: This table shows population and wealth share as well as mean and median net wealth across the income and net wealth distribution. In the first net wealth decile the debt outweight assets and thus the wealth share is negative.

Table A2: Net wealth by socioeconomic characteristics1
	Population share	Conditional mean	Conditional median
	%	EUR thousand
Single household	38.2	178.7	26.7
Two-person household	34.9	323.4	179.0
Three-person household	12.8	348.6	213.3
Household with 4 members or more	14.1	476.7	212.7
Owns main residence	47.6	547.4	333.7
Rents own residence	45.1	59.9	16.0
Uses main residence for free	7.3	74.7	26.2
Bottom 50% of the net wealth distribution	50.0	26.8	15.7
P50-P80 of the net wealth distribution	30.0	251.7	238.3
P80-P95 of the net wealth distribution	15.0	635.0	600.0
Top 5% of the net wealth distribution	5.0	2,192.6	1,642.3
Willingness to take risk: low2	69.2	233.3	118.6
Willingness to take risk: medium	21.5	404.0	145.6
Willingness to take risk: high	9.3	480.2	118.6
Life satisfaction: low3	1.4	262.5	22.5
Life satisfaction: medium	12.8	142.1	13.0
Life satisfaction: high	85.8	316.0	158.0
Poor hand-to-mouth households4	33.1	12.3	7.1
Rich hand-to-mouth households	26.3	335.4	232.3
Non-hand-to-mouth households	40.7	493.7	276.2
Political party preference
ÖVP5	23.6	347.2	197.0
SPÖ	20.8	224.2	97.2
FPÖ	8.5	341.3	75.2
Die Grünen	10.9	319.9	189.4
NEOS	3.4	415.7	139.9
other or none	32.8	263.5	60.3
Source: HFCS Austria 2021, OeNB.
1 This table shows the population shares as well as conditional mean and median net wealth values of each subgroup.
2 The HFCS asked respondents about their risk attitudes on a scale from 1 to 10. We categorize 1-4 as not willing to take risk (low), 5-6 as medium, and 7-10 as willing to take risk (high).
3 The HFCS in Austria asked respondents about their life satisfaction on a scale from 0 to 10. We categorize 0-3 as not satisfied (low), 4-6 as medium, and 7-10 as satisfied (high).
4 We follow Kaplan et al. (2014) to categorize hand-to-mouth households whose financial assets are less than half their yearly gross income. If a household owns real assets in the form of the household’s main residence, other real estate or business assets, it is classified as rich, otherwise as poor hand-to-mouth household.
5 The HFCS asked people about the political party they feel closest to (even if they may not vote for it). The parties listed are those represented in the Austrian parliament at the time of the survey. The question leaves space for non-association.

Table A3: Saving rate of net income by age groups and across the income and wealth distribution
Age	Mean	Median
	%
0–24 years	8.4	7.1
25–39 years	14.4	9.8
40–59 years	16.2	11.3
60 years and older	16.9	12.0
Distribution
1st gross income quintile	12.9	6.8
2nd gross income quintile	13.7	10.5
3rd gross income quintile	17.1	12.9
4th gross income quintile	17.5	13.5
5th gross income quintile	19.2	14.0
1st net wealth quintile	9.7	5.6
2nd net wealth quintile	13.6	9.9
3rd net wealth quintile	14.5	10.7
4th net wealth quintile	18.6	14.7
5th net wealth quintile	24.0	19.3
Source: HFCS Austria 2021, OeNB.
Note: Age refers to the age of the household’s financially knowledgeable person. The savings rate is defined as monthly savings plus debt repayment divided by net monthly household income.

2 Income and wealth characteristics

Table A4: Sources of income across the income and wealth distribution
	Employment		Self-employment		Pension		Rental income
	Participation	Conditional median	Participation	Conditional median	Participation	Conditional median	Participation	Conditional median
	%	EUR thousand	%	EUR thousand	%	EUR thousand	%	EUR thousand
All	55.7	45.2	10.1	14.4	47.3	30.0	4.3	4.9
Income
1st gross income decile	18.2	9.2	9.6	8.9	48.1	14.0	1.4	x1
2nd gross income decile	31.9	19.3	5.0	6.3	67.3	19.7	2.8	x
3rd gross income decile	40.6	24.1	6.3	5.4	60.0	25.4	2.2	x
4th gross income decile	46.6	30.8	7.7	16.4	54.7	31.1	2.4	x
5th gross income decile	47.5	37.6	6.3	11.7	55.9	38.1	3.0	x
6th gross income decile	50.5	43.9	9.9	31.6	52.0	45.2	5.1	x
7th gross income decile	64.1	51.0	12.8	16.9	47.5	51.8	2.6	x
8th gross income decile	80.0	64.3	8.9	17.0	32.4	60.4	4.2	x
9th gross income decile	87.7	77.0	9.9	15.0	27.1	49.3	7.1	x
10th gross income decile	90.1	94.2	24.2	45.6	28.3	44.7	12.7	8.3
Wealth
1st net wealth decile	48.0	24.8	5.7	5.5	38.8	16.4	x	x
2nd net wealth decile	49.6	27.9	6.6	14.4	45.7	21.7	x	x
3rd net wealth decile	54.2	35.0	3.4	30.6	46.6	24.5	x	x
4th net wealth decile	56.7	45.6	5.5	8.6	45.3	36.5	x	x
5th net wealth decile	63.5	57.2	10.2	7.0	42.7	32.0	2.2	x
6th net wealth decile	57.4	59.3	7.2	16.3	50.0	31.8	1.6	x
7th net wealth decile	60.6	64.8	7.9	33.4	43.4	35.6	2.8	x
8th net wealth decile	52.9	59.2	7.2	31.1	53.6	31.8	5.2	x
9th net wealth decile	53.9	58.1	16.0	11.3	61.0	35.7	10.3	4.4
10th net wealth decile	60.3	52.9	31.0	20.8	46.2	37.6	21.0	8.2
Source: HFCS Austria 2021, OeNB.
1 Cells displayed as “x” do not have enough observations to be displayed.
Note: This table shows participation rates as well as conditional median gross income values across income and net wealth deciles. Selected sources of income are displayed.

3 Households main residence

Table A5: Household main residence (HMR) ownership across regions
	Participation	Conditional mean	Conditional median
	%	EUR thousand
Vorarlberg	56.0	584.0	500.0
Tyrol	52.6	770.4	576.0
Salzburg	50.7	398.3	400.0
Upper Austria	50.0	436.5	371.6
Carinthia	53.9	290.9	300.0
Styria	56.9	237.5	200.0
Burgenland	67.7	242.2	200.0
Lower Austria	63.3	242.3	200.0
Vienna	18.9	436.6	317.9
Source: HFCS Austria 2021, OeNB.
Note: This table shows participation rates as well as conditional mean and median values for households’ main residences across provinces in Austria.

4 Mortgages and household vulnerability

Table A6a: Collateralized debt and income
	2021
	%
Share of households with collateralized debt, all households	13.9
Share of households with collateralized debt, 1st income quintile (gross)	3.9
Share of households with collateralized debt, 2nd income quintile (gross)	6.1
Share of households with collateralized debt, 3rd income quintile (gross)	11.4
Share of households with collateralized debt, 4th income quintile (gross)	20.0
Share of households with collateralized debt, 5th income quintile (gross)	28.3
Share of collateralized debt in % of total debt	84.5
Gross income, all households, median (EUR thousand)	43.0
Gross income, households with collateralized debt, median (EUR thousand)	68.8
Source: HFCS Austria 2021, OeNB.
Note: This table shows information about mortgages and income to assess the debt sustainability of households in Austria. We display mortgage participation over the income distribution and the share of mortgages in total debt. Additionally, it can be seen that mortgage holders at the median have higher income than the total population.

Table A6b: Debt burden indicators and vulnerability measures
	2021
	%
Debt to income (DTI),1 median collateralized debt (collateralized debt)	84.1
DTI>=3, in % of households with collateralized debt	16.1
DTI>=3, share of debt held by these households as a percentage of total collateralized debt	46.1
Debt service to income (DSTI),2 median (debt payments for collateralized debt)	11.0
DSTI>=40, in % of households with collateralized debt	3.1
DSTI>=40, share of debt held by these households as a percentage of total collateralized debt	7.9
Loan to value (LTV),3 median (household main residence, HMR)	19.2
LTV>=90, in % of households with collateralized debt on their HMR	3.6
LTV>=90, share of debt held by these households as a percentage of total HMR collateralized debt	17.2
Source: HFCS Austria 2021, OeNB.
1 Debt to income (DTI) is defined as collateralized debt divided by gross income, calculated for households with collateralized debt. The threshold of 3 to indicate potential vulnerability is taken from the literature.
2 Debt service to income (DSTI) is defined as the ratio of the monthly mortgage debt payments to gross household income, calculated for households with collateralized debt. The 40% threshold to indicate potentially vulnerable households is taken from the literature.
3 The loan-to-value ratio (LTV) is derived for households’ main residence only, dividing the current outstanding amount of mortgages on the HMR by the current value of the HMR.

5 Variables for macro models

Question wording can be seen in the online appendix of the methodological report (see https://www.hfcs.at/en/results-tables/hfcs-2021.html).

Table A7a: Wealth transfers
	Participation	Conditional mean	Conditional median
	%	EUR thousand
All inheritances and gifts simple value	40.3	159.2	49.9
All inheritances and gifts net present value (3% interest)	40.3	275.4	98.1
Gifts simple value	15.8	157.7	43.2
Inheritances simple value	27.6	141.9	44.0
Source: HFCS Austria 2021, OeNB.
Note: In the HFCS, wealth transfers are recorded as gifts and/or inheritance types and the value at the time of ownership transfer (simple value). This table shows all the transfers with the value given and calculated as the net present value with an interest rate of 3%. Additionally, this table displays the split between types. Participation rates together with conditional mean and median levels are shown.

Table A7b: Wealth transfers (simple value of all inheritances/gifts) by education level and across the net wealth distribution
	Share of households who have inherited / received a gift	Conditional mean	Conditional median
	%	EUR thousand
Education
Compulsory education or below	34.8	59.8	16.7
Apprenticeship, vocational school	34.8	112.9	43.0
Upper secondary, school-leaving certificate	41.4	204.9	56.5
University, technical college	57.7	210.8	119.5
Distribution
1st net wealth decile	19.7	20.7	4.9
2nd net wealth decile	17.5	11.6	3.7
3rd net wealth decile	22.5	29.4	7.6
4th net wealth decile	29.0	47.1	15.1
5th net wealth decile	36.5	56.4	22.3
6th net wealth decile	34.0	124.0	70.0
7th net wealth decile	42.3	119.7	86.8
8th net wealth decile	63.2	128.6	65.6
9th net wealth decile	61.5	170.3	73.9
10th net wealth decile	76.6	413.2	204.0
Source: HFCS Austria 2021, OeNB.
Note: This table shows all gifts and/or inheritance types and the value recorded at the time of ownership transfer. Participation rates as well as conditional mean and median values are reported. Education refers to the level of education of the financially knowledgeable person.

Table A8: Households who can borrow EUR 5,000
	Share of households who can borrow in %
Distribution
1st gross income decile	43.2
2nd gross income decile	49.6
3rd gross income decile	57.2
4th gross income decile	59.5
5th gross income decile	66.2
6th gross income decile	57.6
7th gross income decile	60.5
8th gross income decile	61.8
9th gross income decile	69.0
10th gross income decile	82.9
1st net wealth decile	28.9
2nd net wealth decile	41.2
3rd net wealth decile	64.9
4th net wealth decile	57.6
5th net wealth decile	58.4
6th net wealth decile	56.9
7th net wealth decile	57.1
8th net wealth decile	75.7
9th net wealth decile	79.5
10th net wealth decile	87.5
Source: HFCS Austria 2021, OeNB.
Note: This table shows the population share of households who report being able to borrow EUR 5,000 from a friend or a relative.

Table A9: Attitudes about risk, trust and the future
	Risk	Trust	Future
	Average
Distribution
1st gross income decile	6.2	5.3	6.2
2nd gross income decile	5.6	5.4	5.6
3rd gross income decile	6.1	5.4	6.1
4th gross income decile	6.1	5.5	6.1
5th gross income decile	6.4	5.6	6.4
6th gross income decile	6.6	5.9	6.6
7th gross income decile	6.6	5.9	6.6
8th gross income decile	6.8	6.3	6.8
9th gross income decile	7.0	6.5	7.0
10th gross income decile	6.1	6.4	6.1
1st net wealth decile	6.1	5.3	6.1
2nd net wealth decile	6.1	5.2	6.1
3rd net wealth decile	6.3	5.4	6.3
4th net wealth decile	6.6	6.0	6.6
5th net wealth decile	6.2	6.0	6.2
6th net wealth decile	6.9	6.1	6.9
7th net wealth decile	6.9	6.5	6.9
8th net wealth decile	6.3	5.9	6.3
9th net wealth decile	5.8	5.9	5.8
10th net wealth decile	6.1	5.8	6.1
Source: HFCS Austria 2021, OeNB.
Note: The HFCS in Austria collects information about people’s attitudes about risk-taking, trust in other people and the future. Respon dents indicate, on a range from 1 to 10, whether they have a very low or very high affinity to risk, whether they trust other people not at all or completely and whether they are not at all or very much worried about the future. The table shows average values across gross income and net wealth deciles.

Table A10a: Preference for taxation by occupation status
	1pp wealth tax and 2pp reduction of income tax	1pp wealth tax and 5pp reduction of income tax
	%
Occupation
Self-employed	59.4	61.8
(Skilled) blue-collar worker	73.0	75.8
White-collar worker	77.5	79.6
Civil servant	63.6	77.0
Farmer	31.4	53.6
Pensioner	74.3	72.2
Unemployed	77.2	85.1
Other	78.5	86.3
Source: HFCS Austria 2021, OeNB.
Note: The question in the HFCS reads “Are you in favor of introducing a wealth tax of 1 percentage point while simultaneously reducing the taxation of income from work by 2 percentage points?” The table shows the percentages of households supporting the idea.

Table A10b: Preference for taxation across the income and wealth distribution
	1pp wealth tax and 2pp reduction of income tax	1pp wealth tax and 5pp reduction of income tax
	% in favor
Distribution
1st gross income decile	75.0	78.0
2nd gross income decile	80.9	75.6
3rd gross income decile	75.4	80.9
4th gross income decile	76.4	79.8
5th gross income decile	73.6	76.7
6th gross income decile	70.4	70.7
7th gross income decile	73.0	74.8
8th gross income decile	72.0	74.4
9th gross income decile	83.3	78.3
10th gross income decile	60.5	65.5
1st net wealth decile	75.4	85.3
2nd net wealth decile	78.9	80.7
3rd net wealth decile	81.8	82.1
4th net wealth decile	80.5	82.5
5th net wealth decile	77.2	73.9
6th net wealth decile	80.9	78.7
7th net wealth decile	81.9	80.8
8th net wealth decile	72.1	70.4
9th net wealth decile	59.9	60.6
10th net wealth decile	52.0	59.6
Source: HFCS Austria 2021, OeNB.
Note: The question in the HFCS reads “Are you in favor of introducing a wealth tax of 1 percentage point while simultaneously reducing the taxation of income from work by 5 percentage points?” The table shows the percentages of households supporting the idea.

The COVID-19 related information was collected with a reference to the years 2020/21 in comparison to 2019, i.e. before the COVI-19 outbreak in Austria. Question wording can be seen in the online appendix of the methodological report (see https://www.hfcs.at/en/results-tables/hfcs-2021.html).

Table A11a: Average health indicators across the income and wealth distributions: In the past four weeks, about how often did respondents feel
	rushed or under time pressure?	down and melancholic?	calm and balanced?	that they have a lot of energy?	strong physical pain?	that they accomplished less in their work or daily activities than they actually wanted to because of physical health problems?	that they were limited in the nature of their activities?	that they accomplished less in their work or daily activities than they actually wanted to because of emotional or psychological problems?	that they did their work or tasks less carefully than usual?	that they were limited in their social contacts, such as with friends, acquaintances, or relatives, due to physical health or emotional problems?
	Average
Distribution
1st gross income decile	3.9	3.5	2.5	3.2	3.7	3.7	3.7	3.8	4.1	4.0
2nd gross income decile	4.2	3.8	2.3	3.1	3.9	3.9	4.0	4.2	4.3	4.3
3rd gross income decile	3.9	4.0	2.4	2.9	4.1	3.9	4.0	4.3	4.6	4.5
4th gross income decile	3.9	4.0	2.3	2.9	4.0	4.0	4.1	4.4	4.5	4.4
5th gross income decile	4.0	4.1	2.3	2.8	4.2	4.2	4.2	4.5	4.6	4.5
6th gross income decile	3.8	4.0	2.3	2.7	4.1	4.0	4.1	4.5	4.6	4.6
7th gross income decile	3.7	4.2	2.3	2.6	4.3	4.3	4.4	4.6	4.7	4.7
8th gross income decile	3.5	4.0	2.6	2.6	4.3	4.0	4.3	4.4	4.7	4.8
9th gross income decile	3.4	4.2	2.7	2.5	4.4	3.8	4.3	4.6	4.8	4.8
10th gross income decile	3.5	4.2	2.7	2.7	4.5	4.3	4.4	4.7	4.7	4.8
1st net wealth decile	3.8	3.5	2.6	3.2	3.9	3.8	3.9	3.9	4.1	4.1
2nd net wealth decile	3.9	4.0	2.3	2.9	4.0	4.1	4.1	4.3	4.5	4.4
3rd net wealth decile	3.9	4.0	2.3	2.9	4.1	4.2	4.2	4.5	4.6	4.5
4th net wealth decile	3.7	4.0	2.4	2.7	4.2	4.0	4.3	4.5	4.7	4.6
5th net wealth decile	3.7	4.1	2.5	2.8	4.2	3.9	4.2	4.4	4.7	4.6
6th net wealth decile	3.9	4.1	2.5	2.8	4.0	3.8	4.0	4.4	4.6	4.7
7th net wealth decile	3.7	4.0	2.5	2.7	4.3	3.9	4.1	4.4	4.6	4.7
8th net wealth decile	3.9	4.2	2.4	2.7	4.2	4.1	4.1	4.5	4.6	4.7
9th net wealth decile	3.8	4.1	2.4	2.9	4.2	4.2	4.2	4.5	4.6	4.6
10th net wealth decile	3.5	4.1	2.3	2.7	4.3	4.3	4.3	4.6	4.6	4.7
Source: HFCS Austria 2021, OeNB.
Note: The HFCS in Austria asked respondents about their health and wellbeing. The answers to these questions relate to the financially knowledgeable person and range from 1 to 5 (1 - always, 2 - often, 3 - sometimes, 4 - almost never, 5 - never). The table shows averages.

Table A11b: Estimated change in net income during the COVID-19 pandemic across the income and wealth distribution
	Decrease by		Change by	Increase by
	25% or more	5% to 25%	less than 5%	5% to 25%	25% or more
All	1.6	4.7	84.4	6.9	2.4
Distribution
1st gross income quintile	3.2	4.5	83.3	5.3	3.8
2nd gross income quintile	1.8	2.3	86.6	6.5	2.8
3rd gross income quintile	1.5	4.3	85.5	7.4	1.4
4th gross income quintile	0.6	6.8	82.0	8.3	2.2
5th gross income quintile	0.9	5.6	84.6	7.0	1.9
1st net wealth quintile	2.1	5.0	81.2	7.4	4.2
2nd net wealth quintile	2.4	5.1	83.3	6.3	2.8
3rd net wealth quintile	1.2	3.2	86.6	7.4	1.7
4th net wealth quintile	0.8	2.7	89.8	6.3	0.4
5th net wealth quintile	1.4	7.4	81.1	7.1	3.0
Source: HFCS Austria 2021, OeNB.
Note: The HFCS asked respondents about changes in net income due to COVID-19. In connection with the infomation on net monthly income, we calculated percentage changes as displayed in this table.

Table A11c: Estimated change in savings during the COVID-19 pandemic across the income and wealth distribution
	Saved less	Saved more	No change
	%
All	20.8	15.8	63.4
Distribution
1st gross income quintile	14.0	18.9	67.1
2nd gross income quintile	24.5	13.7	61.9
3rd gross income quintile	23.3	12.2	64.5
4th gross income quintile	22.8	16.8	60.3
5th gross income quintile	19.4	17.4	63.2
1st net wealth quintile	13.7	21.9	64.4
2nd net wealth quintile	24.7	12.9	62.4
3rd net wealth quintile	17.1	13.7	69.2
4th net wealth quintile	22.9	14.2	62.9
5th net wealth quintile	25.6	16.3	58.1
Source: HFCS Austria 2021, OeNB.

Table A11d: Impact of the COVID-19 pandemic on work
	Lost work	Lost total income	Lost part of income	Reduction of work time because of care duties	Not working due to illness	Short- time work	Working from home
	%
All	3.4	2.2	7.5	0.9	0.9	15.6	18.8
Distribution
1st gross income quintile	5.5	3.4	7.3	0.6	1.1	7.6	5.2
2nd gross income quintile	2.7	1.4	7.0	0.9	0.6	10.8	7.9
3rd gross income quintile	3.7	1.8	6.8	0.8	0.8	13.5	12.7
4th gross income quintile	3.4	1.4	7.8	1.0	0.7	22.9	22.0
5th gross income quintile	1.7	2.9	8.9	1.1	1.1	23.4	46.4
1st net wealth quintile	6.4	2.6	9.2	1.1	1.8	14.8	6.1
2nd net wealth quintile	4.4	1.2	6.5	2.3	0.8	15.8	17.9
3rd net wealth quintile	1.9	1.0	5.5	0.2	0.0	16.1	25.0
4th net wealth quintile	1.8	1.8	4.9	0.3	0.4	16.1	21.2
5th net wealth quintile	2.5	4.3	11.6	0.3	1.2	15.5	23.9
Source: HFCS Austria 2021, OeNB.

Table A11e: Impact of the COVID-19 pandemic on finances
	Delayed payment of credit installment or rent	Re-negotiation of credit terms	Taken out credit	Drawdown of savings or sale of financial assets	Delayed purchase of home, car or other	Reduction of expenses on food, clothes, travel or other consumption goods and services
	% as a share of households experiencing an income loss due to COVID-19
All	4.5	1.3	3.8	67.1	7.5	44.5
Distribution
1st gross income quintile	11.9	5.1	8.4	39.4	12.7	65.9
2nd gross income quintile	4.6	0.0	0.0	55.6	8.5	64.8
3rd gross income quintile	8.8	4.1	0.0	49.0	16.4	63.9
4th gross income quintile	4.3	0.0	4.5	79.2	4.9	43.3
5th gross income quintile	1.1	0.0	2.8	76.2	5.3	29.1
1st net wealth quintile	15.0	6.1	4.6	40.0	13.2	74.4
2nd net wealth quintile	7.2	0.0	5.3	80.1	16.2	43.7
3rd net wealth quintile	0.0	0.0	3.2	82.4	2.0	34.8
4th net wealth quintile	0.0	0.0	3.7	77.5	2.4	35.5
5th net wealth quintile	3.4	1.9	2.4	43.6	7.2	44.7
Source: HFCS Austria 2021, OeNB.

Table A11f: Convincing argument for wealth tax against the backdrop of COVID-19
	The gap between the rich and the poor in Austria is too large, and a wealth tax could help reduce it	The wealthy have become richer in recent years; it’s time for them to give something back	If tax increases are necessary, it is better to tax wealth rather than income from employment	The government needs to plug the budget hole caused by the COVID-19 pandemic	A wealth tax would contribute to generating funds for government services	Introducing a wealth tax now would help minimize the tax burden for future generations	None of the arguments
	%
All	66.2	58.6	56.6	50.3	42.3	36.9	10.5
Distribution
1st gross income quintile	66.6	67.2	54.2	44.6	36.2	25.2	9.6
2nd gross income quintile	61.6	64.8	59.6	45.4	35.4	28.4	12.7
3rd gross income quintile	66.6	61.4	53.2	52.1	39.4	37.2	9.5
4th gross income quintile	65.7	53.6	56.0	51.4	44.2	39.9	10.7
5th gross income quintile	70.5	45.7	60.0	57.8	56.7	54.1	10.1
1st net wealth quintile	66.7	68.6	60.5	45.2	40.2	26.6	7.8
2nd net wealth quintile	68.5	64.3	60.7	51.1	41.1	34.1	6.9
3rd net wealth quintile	69.1	51.3	56.9	58.1	47.6	44.9	9.4
4th net wealth quintile	70.0	55.1	54.3	50.1	45.6	42.1	10.5
5th net wealth quintile	56.8	53.5	50.6	46.8	37.2	37.0	18.0
Source: HFCS Austria 2021, OeNB.
Note: The question reads: “There are many arguments both for and against the introduction of a wealth tax in Austria. Which of the arguments listed below do you find convincing in favor of implementing a tax on net assets?”

Table A11g: Life satisfaction
	Average
Distribution
1st gross income decile	7.1
2nd gross income decile	7.6
3rd gross income decile	7.9
4th gross income decile	7.8
5th gross income decile	8.0
6th gross income decile	8.2
7th gross income decile	8.2
8th gross income decile	8.1
9th gross income decile	8.3
10th gross income decile	8.6
1st net wealth decile	6.8
2nd net wealth decile	7.6
3rd net wealth decile	7.9
4th net wealth decile	8.3
5th net wealth decile	8.1
6th net wealth decile	8.0
7th net wealth decile	8.0
8th net wealth decile	8.2
9th net wealth decile	8.4
10th net wealth decile	8.4
Source: HFCS Austria 2021, OeNB.
Note: The HFCS asked respondents how satisfied they are in general with their lives. The values run from 0 (totally dissatisfied) to 10 (completely satisfied). The table displays average values.

1 Oesterreichische Nationalbank, Research Section, pirmin.fessler@oenb.at, peter.lindner@oenb.at, martin.schuerz@oenb.at. Opinions expressed by the authors of studies do not necessarily reflect the official viewpoint of the OeNB or the Eurosystem.

2 A more detailed definition of net wealth can be found in previous reports (see e.g. Fessler et al., 2018).

3 The fourth wave of the Eurosystem HFCS was conducted in the following euro area countries: Belgium, Germany, Estonia, Ireland, Greece, Spain, France, Italy, Cyprus, Luxembourg, Latvia, Lithuania, Malta, the Netherlands, Portugal, Slovenia, Slovakia and Finland. Additionally, Czechia, Croatia, Denmark, and Hungary took part.

4 The question reads: “Looking at your household’s entire net wealth, where in the distribution would you classify your household on a scale from 1 to 10 (1 denotes the bottom 10% category with the lowest wealth and 10 the top 10% with the highest wealth in Austria)?”

5 For reasons of simplicity, we here represent the mean-to-median ratio as a simple division of the estimated mean by the estimated median. The underlying means and medians were estimated based on the five multiply imputed datasets.

6 In the HFCS for Austria, real estate property of farming households that is part of their agricultural business is recorded under investments in self-employment businesses. On the other hand, some other real estate assets also qualify as property for business use.

7 Note that we use the rough household level estimate for available total net income here and not the detailed HFCS gross income based on many items.

8 The HFCS allows for many other combinations, such as analyzing pensions or private transfers separately.

9 Fully rational behavior is a standard assumption in many economic models. However, it is falsified by empirical evidence.

10 Data of the DWA have not been published yet and are only available internally. This information is expected to become publicly available for the public including the scientific community within the SNA in autumn 2023. We make use of the most recent version of the experimental DWA-data as of May 2023.

11 For complete details of the methodology, see Expert Group on Linking macro and micro data for the household sector (2020) and Engel et al. (2022).

12 This additional information is published regularly by e.g. Forbes and the Austrian Trend magazine.

13 Alternatively, also a multivariate calibration approach could be applied.

14 The Bundesbank published these data for Germany in Deutsche Bundesbank (2022).

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