Masaryk University Economic Seminars

Non-take-up (NTU) of social benefits is usually explained through barriers at the individual level, such as lack of information, stigma, or administrative burden. This study asks whether such household characteristics can account for differences in benefit take-up across countries, using harmonized EU-SILC 2022 data linked to EUROMOD microsimulation outputs reflecting the tax and benefit rules in place in 2021. Take-up of two benefit types is analyzed across European countries: housing- and family-related means-tested benefits, focusing on whether an eligible household claims the benefit at all. Firth penalized logistic regression is used to address convergence problems caused by very low variation in take-up in several countries, combining a broad set of household level predictors with country fixed effects. A McFadden pseudo R2 decomposition indicates that variation between countries accounts for roughly 60% of the explained variation in take-up for both benefit types, while household characteristics contribute comparatively little beyond this. Reported non-take-up of housing benefits is very high across most sampled countries; this may partly reflect genuine non-claiming behavior and partly known difficulties in simulating eligibility for housing benefits from survey data. Non-take-up of family benefits varies far more widely across countries, from around 5% to nearly 80%. The findings point to institutional and systemic factors, such as benefit design, administrative procedures, and national context, as the primary drivers of non-take-up, challenging accounts that locate the problem mainly in individual household behavior.

Our research measures emotions in US newspapers related to economic policy. The motivation of the study is to examine whether emotion decomposition provides information beyond conventional news-based uncertainty measures and sentiment indices, and could improve financial-market monitoring and forecasting. After emotion identification, we construct an emotion-related (sentiment) index and examine its impact on EPU, VIX, SP 500, and USD using the BVAR model. Preliminary results show that increases in negative emotions lead to persistent increases in the Economic Policy Uncertainty index and the VIX. In contrast, their effects on S&P 500 and US dollar returns are smaller, negative, and largely transitory. Positive-emotion shocks produce weaker and less precisely estimated responses.