Elisa Cisotto , Free University of Bozen-Bolzano
Giulia Cavrini, Free University of Bozen-Bolzano
The purpose of this research is to study quality of life (QoL) and related factors in a group of older-adult subjects, and to propose quantile regression models as alternative method of analysis. Standard regression techniques are only able to give an incomplete picture of the relationship between QoL and related factors since they implicitly focus on mean outcomes. Using cross-sectional data from the Survey on Health, Ageing and Retirement (SHARE) for the year 2013, we apply quantile regressions to analyze the associations of a set of explanatory variables with different quantiles of the QoL distribution and compare these results with a standard OLS regression. General results show a decreasing importance of socio-economic conditions and social factors with increasing quantiles of QoL. Associations between QoL, health condition and cognitive functioning, as well as country of residence are, on the contrary, pretty stable over quantiles. As a next stage of the current study, we plan to update the analysis to the more recent SHARE data (wave 7 – 2017) and to increase the sample of analysis, when necessary, pooling multiple waves of SHARE.
Presented in Session P2. Poster Session Ageing, Health and Mortality