Poset-Based Analysis of Mental Well-Being of Immigrants and Natives in Europe

Among subjective well-being (SWB) measures, mental well-being emerges as a broad, intricate and multidimensional concept with significant policy implications. Aim of this paper is to classify groups of individuals based on age, income and country of residence, distinguished by sex and immigrant generation, and according to two indicators of mental well-being. To compare pairs of subpopulations, we adopt the Fuzzy First Order Dominance on Partially Ordered Sets (F-FOD on posets). This methodology operates under the assumption that the set of all possible profiles within a population is partially ordered, meaning some combinations of modalities are comparable while others are not. It enables the assessment of the probability that an individual randomly chosen from one sub-population surpasses an individual selected from another sub-population. We use data from the cross-sectional European Quality of Life Survey (EQLS) of 2016, a unique pan-European survey. The analysis shows interesting results that, on the one hand, confirm previous findings on well-being’s international rankings, and, on the other hand, show that non-aggregative methodologies are important for SWB, since they take into account the different criteria individuals use in evaluating their own outcomes in surveys.