901.3
Effect of Objective Well-Being Factors and Satisfactions in Different Domains on Subjective Well-Being

Tuesday, 17 July 2018: 16:00
Location: 201B (MTCC NORTH BUILDING)
Oral Presentation
Annika LEHMUS-SUN, University of Helsinki, Finland
The great amount of academic and political interest towards subjective well-being has caused also a demand for understanding it, hence I have conducted a longitudinal data analysis about factors that predict one’s subjective well-being. The analysis is focusing also on the correlations of different types of both subjective and objective well-being indicators.

The indicators for subjective well-being in my study are happiness and life satisfaction. Further, the indicators for objective well-being are operationalized from two theories. The one is Richard Layard’s (2011) construction of happiness: “Seven Causes for Happiness”, and the other one is the capability approach by Amartya Sen (1993). The Seven Causes for Happiness are family relation- ships, financial situation, work, community and friends, health, personal freedom and personal values; and the capabilities are mostly about satisfaction in different domains in life (satisfaction with partner, job, household income, social life, neighborhood, and leisure time), and also financial manageability, health limitations, ability to vote, voluntary group and political group membership. The capabilities help paying attention to the relationship between the outcomes and the opportu- nities on one’s subjective well-being.

The data is drawn from the British Household Panel Survey (BHPS), which is a nationally representative longitudinal survey of nearly 10 000 individuals over 16 years of age in the United King- dom. The analysis based on 12 waves of the BHPS, which enables to explore whether the objective well-being factors, that might have changed in the life of an individual, have an impact in one’s subjective well-being and moreover, the difference between happiness and life satisfaction. Analyses were performed using a linear mixed-effects model to analyse the correlation between objective well-being indicators and life satisfaction and happiness at different points in time.