Deprivation, social mobility considerations and life satisfaction: A comparative study of 33 European countries

Abstract

This study aims to provide a comparative analysis between non-transition and transition countries, with focus on exploring the life satisfaction costs of deprivation aspects, i.e., material, subjective and relative deprivation. For the latter, we calculate the Gini index at the regional (city) level since the Gini index at the country level is unable to capture the influence of income inequality on life satisfaction for both sets of countries. A negative association between these measures and life satisfaction is suggestive of deprivation measures being quality-of-life important considerations in the EU and neighbouring candidate countries. The relative importance of such indicators is also of particular interest because it is driven by social mobility considerations. The study is based on a comparative analysis of data taken by nationally representative household database from the 2016 European Quality of Life Survey. We evaluate the hypotheses using a two-level linear mixed-effects model of individual responses collected in 33 European countries (28 EU countries plus Albania, Montenegro, North Macedonia, Serbia, and Turkey). Estimates are generated for the pooled sample and separately for the non-transition (West-EU) and transition post-communist (East-EU and non-EU) countries. The results suggest that there are significant life satisfaction costs attached to all the three aspects of deprivation. However, the relative importance of subjective deprivation, as a measure of income inequality at the city level, is significantly larger than material and subjective deprivation, even after we control for equivalised household income. This relationship is more pronounced for transition countries as compared to non-transition ones.

Assessing relative contribution of Environmental, Behavioural and Social factors on Life Satisfaction via mobile app data

“…Thus a low LS can lead to a vicious cycle, and a continual longitudinal decline in wellbeing [5]- [8]). Such insecurity can also lead to a decrease in social participation, limiting a person's ability to engage socially due to either cost or stigma [17], [25], further increasing social isolation and loneliness [23].…”

“…Being part of a dense social network improves LS and an individual's sense of belonging [30]; and while not always true, being part of a sparse social network generally correlates to lower overall self-reported scores of LS. Other significant socio-economic factors that impact LS are noted in the literature, including: Age [31]- [33]; Income [34]; Diet [35]; and wider environmental factors such as public transport access, crime and greenspace access [25], [36], [37].…”