Assessing subjective well-being in wide populations. A posetic approach to micro-data analysis

The subjective measures of well-being are mainly constructed on ordinal indicators. Therefore, the choice of the correct method to synthesize the information collected becomes fundamental. This is particularly true for studies involving large populations of respondents, as in the case of official statistical. In this study, we deal with the analysis of subjective well-being data from a European harmonized official statistical survey: the European Union Survey on Income and Living Conditions (Eu-SILC). We take into account the ordinal nature of items. In particular, we propose a two-step synthesis process: first, we address the synthesis of the indicators used to measure the emotional state, and then move on to the synthesis of three dimensions of the subjective well-being, namely life satisfaction, meaning of life and emotional status. Finally, we propose an analysis of the differences in well-being assessment among different sub-populations of respondents. Our analysis intends to safeguard the multidimensionality of the phenomenon, applying the Partially Ordered Set methodology to the micro-data analysis.