Pension in the national accounts and wealth surveys: how do they impact economic measures?

Wealth aggregates implied by the Household Finance and Consumption Survey (HFCS) usually yield much lower amounts than macroeconomic statistics reported in the National Accounts. An important source of this gap may be the under-representation of the wealthiest households in the HFCS. This article therefore combines a semi-parametric Pareto model estimated from top survey data and observations from rich lists with a non-parametric stratification approach to quantify the impact of the missing wealthy households on component-specific micro-macro gaps. We find that unadjusted micro data substantially underestimates wealth inequality. The largest effects are documented for equity. For other components, the missing wealthy explain less than ten percentage points of the micro-macro gap. We find that differences in oversampling strategies limit the cross-country comparability of unadjusted survey-implied wealth distributions and that our top tail adjustment leads to measures that are internationally better comparable.

While taxes on wealth for a long time played only a marginal role in the public finance and taxation literature, the increase of wealth inequality and concentration in many EU countries has spurred new interest in wealth taxation. At the same time, recurrent net wealth taxes have almost completely disappeared in Europe, inter alia due to fears of asset and taxpayer migration. The paper provides estimates of the revenue that could be raised from an EU-wide net wealth tax enabling the containment of migration responses, using data from the Household, Finance and Consumption Survey (HFCS). To account for differential non-response, we augment the HFCS with data from the Forbes rich list as well as national rich lists and replace the top tail of the wealth distribution according to the HFCS by an estimated Pareto distributed top tail. To account for under-reporting we scale aggregate financial assets in the HFCS to match their counterparts outlined in the National Accounts. We estimate that a moderately progressive net wealth tax levied at a rate of 1% on net wealth between € 1 and € 5 million, and 1.5% on wealth above € 5 million, could raise between € 165 and € 177 billion after accounting for avoidance and evasion responses. Such an EU harmonized net wealth tax would affect only a small fraction of households, ranging between 0.41% in Latvia and 8.65% in Belgium.

The paper presents the main results of the Eurosystem’s Household Finance and Consumption Survey (HFCS) with an emphasis on the data for Italy in the international context. The paper examines households’ socio-demographic characteristics, assets and income distribution, participation in real and financial assets and indebtedness levels. The results for Italy reveal a mean household gross income below the euro-area average. The concentration of income in Italy is roughly positioned at a median position, while the index of relative poverty is comparatively high. Among the main countries of the euro area, Italy shows the same average level of net worth per capita of Spain and slightly higher levels than those of France and Germany, in line with the high savings rates that characterized Italian households over the last few decades, although this trend has decreased in recent years. Finally, Italy shows the lowest percentage of indebted households.

For the first time, the Household Finance and Consumption Survey (HFCS) dataset enables researchers to have a detailed insight into the relationship between wealth composition and the characteristics of households for the euro area countries. The HFCS is a complex survey accounting for survey design, non-response and coverage problems by providing specific weighting schemes and multiple implicates. This paper investigates the differences between risky asset holders and non-holders in a set of selected countries in the euro area by giving a comprehensive cross-country comparison of their wealth and socio-economic status. The findings show a substantial inequality between these two groups associated with their wealth, real estate ownership and debt level across the euro area countries. However, most of the differences can be reduced to a handful of relevant covariates. In particular, the focus of this paper is on the relationship between background risks and risky assets in the German-speaking countries in the HFCS dataset. So far, Austria and Germany lacked a qualitative dataset of such a scale and detail prior to the HFCS in order to answer questions concerning household risky assets. A logistic model and a GLM with the inverse Gaussian distribution are applied within the complex survey design to explore relevant covariates explaining the probability and the investment level of risky asset holdings. The logistic model for Austrian and German households suggests that housing risk is a negligible and insignificant factor when deciding to invest in risky assets, while credit constraint, occupation-linked income risks and entrepreneurial risks are major negative factors. However, none of these background risk factors are found to be significant when the level of investment is concerned.

Macroeconomic aggregates on households’ wealth have a long tradition and are widely used to analyse and compare economies, yet they do not provide any information about the distribution of assets and liabilities within the population. The Household Finance and Consumption Survey (HFCS) constitutes a rich source of micro data that can be used to link macro aggregates with distributional information to compile Distributional National Accounts for wealth. Computing aggregates from this survey usually yields much lower amounts than what is reported by macroeconomic statistics. An important source of this gap may be the lack of the wealthiest households in the HFCS. This article combines a semi-parametric Pareto model estimated from survey data and observations from rich lists with a stratification approach making use of HFCS portfolio structures to quantify the impact of the missing wealthy households on instrument-specific gaps between micro and macro data. We analyse data for Austria and Germany, and find that adjusting for the missing wealthy pushes up inequality even further, increases instrument-specific aggregates, has large effects on equity, but explains less than ten percentage points of the micro-macro gap for most other instruments. Additionally, we document that some countries’ lack of an oversampling strategy for wealthy households limits the cross-country comparability of wealth inequality statistics.

We explore the prospects for using the Eurosystem Household Finance and Consumption Survey (HFCS) dataset as an underlying micro-database for the EU tax-benefit model, EUROMOD. This will allow expanding the policy domains currently covered in EUROMOD with dimensions like wealth taxation, incentives for wealth accumulation and asset tests determining benefit eligibility. As the HFCS only contains gross income amounts which are not suitable for distributive analysis, the purpose of this paper is to derive net incomes by simulating the gross-to-net transition with EUROMOD taking into account all important details of the social security and personal income tax system. In order to identify the issues and illustrate their importance a trial database for Belgium and Italy is constructed

This paper argues that the cumulative causation processes between wealth and power risk leading to an escalation of wealth inequality. Piketty's historical description of this development from administrative data for individual countries is corroborated with new survey data for the eurozone, the Household Finance and Consumption Survey (HFCS). Wealth is extremely unequally distributed in the eurozone – much more so than income. Furthermore, we provide a multi-faceted picture of wealth distribution in Europe using the socio-economic characteristics available in the HFCS, and we show that inheritances are the single most important factor for wealth inequality. The structural power to shape economic and political institutions is thus ever more concentrated. Finally, we discuss three channels through which the unequal distribution of private assets may affect power relations and economic activity.

This article compares the results of Austria’s Household Finance and Consumption Survey (HFCS) on savings deposits and estimates on total financial assets with administrative records from the national accounts for the household sector. The microdata that are newly generated through the HFCS and the detailed (internally available) breakdown of savings deposits in the existing macrodata (financial accounts) lend themselves to a more in-depth analysis of the similarities and differences in these two sources. Comparing the data shows that the HFCSbased aggregate estimates are lower than the financial accounts data, which is in line with evidence from the literature. The article also shows, however, that the survey adequately captures the underlying patterns at the microlevel in terms of the overall financial portfolio allocation and the distribution of savings deposits over detailed breakdowns. Moreover, a simulation based on the HFCS data demonstrates the effect that the inclusion of savings deposits in the most affluent tail of the distribution has on common statistics. Undercoverage above all of the upper deposit ranges suggests an underestimation or bias in the statistics. This underestimation, however, can be shown to be relatively minor, particularly in the case of robust statistical measures, such as the median or percentile ratios.

Household Finance and Consumption Survey (HFCS) is a survey focused mainly on mapping financial and assets situation of households. In Czechia, the survey has been conducted annually since 2020 under the name Finanční situace domácností (FSD). The article focuses on the implementation of the survey in the Czech setting, mainly describing the cooperation between the Czech Statistical Office and the Czech National Bank. A particular attention is paid to the methodological aspect of FSD as well as to the survey’s main outcomes, primarily the net wealth indicator. The integration of FSD into the EU-SILC (European Union – Statistics on Income and Living Conditions) survey enables annual data collection and publication of main results, as well as the reduction of respondent burden.

Using the Household Finance and Consumption Survey (HFCS), a large micro-level dataset on households' wealth in fifteen euro area countries, this paper explores how households allocate their assets. We derive stylized facts on asset participation as well as levels of asset holdings and investigate the systematic relationships between household characteristics and asset holding patterns. Real assets make up the bulk of total assets. Whereas ownership of the main residence varies strongly between countries, the value of the main residence tends to be the major asset for home-owners and is a significant part of total assets in all countries. While almost all households hold safe financial assets, a low share of households holds risky assets. The ownership rates of all asset categories generally increase with wealth (and income). The significance of inheritances for wealth accumulation is remarkable and underlines its key role in the process of persistent wealth inequality. We tentatively link differences in asset holding patterns across countries to differences in institutions, such as mortgage market institutions and house price-to-rent ratios.

The results from the second wave of the Eurosysystem’s Household Finance and Consumption Survey (HFCS) indicate that Cyprus households experienced very large falls in their incomes and value of real assets between 2009/2010 and 2013/2014. However, despite their worsening financial situation households largely maintained their relatively high level of consumption during the crisis years from 2012 onward by taking on more debt and running down their financial assets. This relative failure of Cyprus households to adjust their expenditures and repair their balance sheets during recent years has resulted in huge debt problems for many households and their creditors. Indeed, HFCS estimates indicate that the ratio of required debt payments to income for Cyprus indebted households reached 35.7% in 2014 and was an overwhelming 64.1% for the least-wealthy bottom 20%. Policy recommendations for dealing with the serious financial difficulties of households are advanced including a program to write-off the debt of households which do not have the ability to repay.

Using the first wave of the Eurosystem Household Finance and Consumption Survey (HFCS), a large micro-level dataset on households’ balance sheets in 15 euro area countries, this paper explores how households allocate their assets. We derive stylised facts on asset participation as well as levels of asset holdings and investigate the systematic relationships between household characteristics and asset holding patterns. Real assets make up the bulk of total assets. Whereas ownership of the main residence varies strongly between countries, the value of the main residence tends to be the major asset for homeowners and represents a significant part of total assets in all countries. While almost all households hold safe financial assets, a low share of households holds risky assets. The ownership rates of all asset categories generally increase with wealth (and income). The significance of inheritances for home ownership and holding of other real estate is remarkable. We tentatively link differences in asset holding patterns across countries to differences in institutions, such as mortgage market institutions and house price-to-rent ratios.

Income and wealth surveys are usually affected by unit non‐response and reporting errors, which contribute to a mismatch with macroeconomic figures from national accounts. In this paper, we develop a novel allocation method to address these two issues simultaneously, when only limited external information is available. The proposed approach combines information from a power law (Pareto) model with imputation procedures based on calibration. We apply the proposed simultaneous approach to produce distributional indicators for four Euro‐Area countries that are consistent with their national accounts. In particular, we use data from the 2014 Finnish, French, German, and Italian Household Finance and Consumption Survey and rich list data from Forbes or national press sources, along with household sector aggregates from national accounts, as auxiliary sources of information. A bootstrap procedure is also applied to evaluate the precision of the final estimates.

Using microdata from the Household Finance and Consumption Survey (HFCS), this study examines the role of inheritance, income and welfare state policies in explaining differences in household net wealth within and between euro area countries. First, about one-third of the households in the 13 European countries we study report having received an inheritance, and these households have considerably higher net wealth than those which did not inherit. Second, regression analyses on households' relative wealth position show that, on average, having received an inheritance lifts a household by about 14 net wealth percentiles. At the same time, each additional percentile in the income distribution is associated with about 0.4 net wealth percentiles. These results are consistent across countries. Third, multilevel cross-country regressions show that the degree of welfare state spending across countries is negatively correlated with household net wealth. These findings suggest that social services provided by the state are substitutes for private wealth accumulation and partly explain observed differences in levels of household net wealth across European countries. In particular, the effect of substitution relative to net wealth decreases with growing wealth levels. This implies that an increase in welfare state spending goes along with an increase—rather than a decrease—of observed wealth inequality.

Using microdata from the Household Finance and Consumption Survey (HFCS), this study examines the role of inheritance, income and welfare state policies in explaining differences in household net wealth within and between euro area countries. First, about one third of the households in the 13 European countries we study report having received an inheritance, and these households have considerably higher net wealth than those which did not inherit. Second, regression analyses on households' relative wealth position show that, on average, having received an inheritance lifts a household by about 14 net wealth percentiles. At the same time, each additional percentile in the income distribution is associated with about 0.4 net wealth percentiles. These results are consistent across countries. Third, multilevel cross-country regressions show that the degree of welfare state spending across countries is negatively correlated with household net wealth. These findings suggest that social services provided by the state are substitutes for private wealth accumulation and partly explain observed differences in levels of household net wealth across European countries. In particular, the effect of substitution relative to net wealth decreases with growing wealth levels. This implies that an increase in welfare state spending goes along with an increase - rather than a decrease - of observed wealth inequality. JEL Classification: D30, D31