WHOCOUNTS · Who Counts? Incorporating a ‘Missing Minority’ to Re-examine the Profile, Drivers and Depth of Poverty across Europe

A non-trivial minority of the de facto population are currently ‘missing’ from income surveys used to construct official statistics on poverty across Europe. WHOCOUNTS will correct for noncoverage error in official EU statistics to better understand the changing profile, drivers and depth of poverty across Europe. Whilst those living outside of private households are often part of the inferential population in poverty debates, they are not part of the target population and thus sampling frame of European Union Statistics on Income and Living Conditions (EU-SILC). This undermines our ability to examine the full incidence, composition and causes of poverty because many of this ‘missing minority’ exhibit some of the worst social outcomes across Europe. Much more than merely technical or pragmatic, such practices reflect a set of theoretical and normative judgments about who counts when it comes to researching poverty and social policy. Through novel analysis of hitherto fragmented data, WHOCOUNTS will re-examine poverty across 8 European countries that differ in their noncoverage, demographics, low-income dynamics, and policy interventions. Drawing on adjusted and unadjusted EU-SILC datasets, this project will improve the accuracy of poverty estimates and nuance explanations of (extreme) poverty across divergent welfare regimes, by complementing multivariate regression techniques with (fuzzy set) qualitative comparative analyses. Capitalising on the analytical potential of set-theoretic approaches, the project will transform our understanding of the overall shape and conjunctural causes of poverty across Europe, providing new and necessary information on the social groups often rendered invisible through official statistics. As such, this project promises a step change in our conceptual, methodological and substantive analysis of (extreme) poverty, and will offer future lessons on how poverty statistics can be improved to support better-informed policy interventions.