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Economic shocks test the resilience of families around the world. Lockdowns, extended periods of unemployment, and inflation challenge the capabilities of private households to maintain their living standards whilst keeping their budgets in balance. Asset poverty is a concept invoked frequently to measure the capacity of private households to mitigate income loss by relying exclusively on their savings. In contrast to conventional asset poverty measures, we quantify the combined cushioning effect of private and public safety nets. Highlighting the importance of public safety nets and familial networks, this article devises a modified concept of asset poverty: Rather than purely simulating a household's asset decumulation without replacement income, the modified indicator accounts for replacement income in a static setting. The empirical assessment of modified asset poverty in Europe and America combines harmonised microdata on household finances with simulations of institutional rules set by social insurance systems. Our results reveal how differences in social relations and institutional rules shape cross‐country variation in the vulnerability of private households. We find that, in contrast to the US, where the asset poverty of families is particularly low, households in most European countries are less vulnerable because generous social security systems coexist with low private assets. However, in some European countries, benefit generosity decreases the longer income losses last, exposing time dynamics in vulnerability. Complementing social insurance mechanisms, in countries such as Greece, households are more likely to receive financial support from family or friends. Cross‐national heterogeneity in vulnerability suggests that a shock may have different implications across countries.

AbstractWe analyse the nature of robust determinants of differences in democracy levels across countries taking explicitly into account uncertainty in the choice of covariates and spatial spillovers. We make use of recent developments in Bayesian model averaging to assess the effect of a large number of potential factors affecting democratisation processes and account for several specifications of spatial linkages. Our results indicate that spatial spillovers are present in the data even after controlling for a large number of geographical covariates. Addressing the determinants of democracy without modelling such spillovers may lead to flawed inference about the nature of the determinants of democratisation processes. In particular, our results emphasise the role played by Muslim religion, population size, trade volumes, English language, natural resource rents, GDP per capita, being a MENA country and the incidence of armed conflicts as factors affecting democracy robustly.

This paper analyzes the mismatch of capital income information between household surveys and macro aggregates in the Eurozone. We contrast data from recent EU-SILC and HFCS waves with Eurostat national accounts for single components of capital income. We find a considerable gap between micro and macro data even when carefully considering comparability issues. On average, EU-SILC and HFCS cover only 26% and 22% of national accounts totals in the Eurozone countries. We further assess which amount of this gap that can be traced back to (a) the undercoverage of the top in survey data and (b) general underreporting of capital income across the distribution. To calculate augmented capital incomes, we utilize wealth information from HFCS and apply Pareto estimations and varying rates of return to capital.

The paper analyses the sources of income measurement error in surveys with a unique data set. We use the Austrian 2008-2011 waves of the European Union "Statistics on income and living conditions" survey which provide individual information on wages, pensions and unemployment benefits from survey interviews and officially linked administrative records. Thus, we do not have to fall back on complex two-sample matching procedures like related studies. We empirically investigate four sources of measurement error, namely social desirabil- ity, sociodemographic characteristics of the respondent, the survey design and the presence of learning effects. We find strong evidence for a social desirability bias in income reporting, whereas the presence of learning effects is mixed and depends on the type of income under consideration. An Owen value decomposition reveals that social desirability is a major expla- nation of misreporting in wages and pensions, whereas sociodemographic characteristics are most relevant for mismatches in unemployment benefits.

The paper analyses the sources of income measurement error in surveys with a unique data set. We use the Austrian 2008-2011 waves of the European Union 'Statistics on income and living conditions' survey which provide individual information on wages, pensions and unemployment benefits from survey interviews and officially linked administrative records. Thus, we do not have to fall back on complex two-sample matching procedures like related studies. We empirically investigate four sources of measurement error, namely social desirability, sociodemographic characteristics of the respondent, the survey design and the presence of learning effects. We find strong evidence for a social desirability bias in income reporting, whereas the presence of learning effects is mixed and depends on the type of income under consideration. An Owen value decomposition reveals that social desirability is a major explanation of misreporting in wages and pensions, whereas sociodemographic characteristics are most relevant for mismatches in unemployment benefits.

"In diesem Beitrag wird die Einkommensverteilung in Österreich unter Berücksichtigung von Vermögenseinkommen analysiert. Während Administrativdaten eine gute Erfassung von Einkommen aus Erwerbstätigkeit bieten, können Informationen zu Kapitaleinkünften lediglich aus entsprechenden Haushaltserhebungen gewonnen werden. Daten aus den Erhebungen EU-SILC und HFCS geben Aufschluss darüber, welche Rolle Vermögenseinkommen in einer Gesamtbetrachtung der Haushaltseinkommen spielen. Die Ergebnisse zeigen, dass zwar drei Viertel der Haushalte Vermögenseinkünfte in irgendeiner Form aufweisen, allerdings nur ein sehr geringer Prozentsatz der Haushalte von diesen Zuflüssen den Lebensunterhalt bestreiten kann. Die Verteilung der Vermögenseinkommen ist dementsprechend ungleich und stark konzentriert. Ein relevanter Beitrag dieser Einkommensart zu den Einkünften aus Erwerbstätigkeit ist ab dem 90. Perzentil zu verzeichnen, im obersten Prozent machen Einkünfte aus Vermögen rund ein Drittel des Gesamteinkommens aus." (Autorenreferat)

Das Ziel des Projektes ist es, unterschiedliche Lebensrealitäten und Spannungsfelder in der Europäischen Union sichtbar zu machen. Der Fokus liegt dabei auf Lohnunterschieden nach Berufen und Ländern. Mittels interaktiver Website wird ein niedrigschwelliger Einstieg in das Thema geboten und diese Unterschiede für eine breite Öffentlichkeit erforschbar gemacht. Das Onlineprojekt lädt zum selbstständigen Entdecken von Inhalten ein, beispielsweise von Lohndifferenzen nach Geschlecht oder typischen Berufen (Ärzt_innen, Reinigungskräfte, Büroangestellte, etc.) Begleitet wird dieser Prozess durch die Darstellung von ökonomischen und institutionellen Rahmenbedingungen, etwa Lebenserwartung oder Schadstoffbelastung. Das Projekt bietet für diese Lebenslagen und -realitäten Lösungsvorschläge an, die zu einer Verbesserung der europäischen Integration beitragen können.

This article investigates the quality of register data in the context of a standardized quality framework. The special focus of this work lies on the assessment of census data and how to deal with uncertainty that arises from multiple sources (registers). To take the uncertainty associated with support and conflict between several registers into account, Dempster–Shafer's theory of evidence is applied. This 'fuzzy' approach allows us to investigate the quality of databases with multiple underlying sources for a single attribute and to provide both quality measures and plausibility intervals.