In the literature on Sen’s capability approach, studies focussing on the empirical measurement of conversion factors are comparatively rare. We add to this field by adopting a measure of “conversion efficiency” that captures the efficiency with which individuals convert their re-sources...

Standard regression techniques are only able to give an incomplete picture of the relationship between subjective well-being and its determinants since the very idea of conventional estimators such as OLS is the averaging out over the whole distribution: studies based on such regression...

There is an ambiguity in Amartya Sen's capability approach as to what constitutes an individual's resources, conversion factors and valuable functionings. What we here call the "circularity problem" points to the fact that all three concepts seem to be mutually endogenous and interrelated. All...

Despite lower incomes, the self-employed consistently report higher satisfaction with their jobs. But are self-employed individuals also happier, more satisfied with their lives as a whole? High job satisfaction might cause them to neglect other important domains of life, such that the...

We use a panel vector autoregressions model to examine the coevolution of changes in happiness and changes in income, health, marital status as well as employment status for the British Household Panel Survey (BHPS) data set. This technique allows us to simultaneously analyze the impact of the...

Is the activity of volunteering something that benefits the volunteer as well as the recipient of the volunteer's activities? We analyze this relationship and apply matching estimators to the large- scale British Household Panel Survey (BHPS) data set to estimate the causal impact of...

Unemployment has been robustly shown to strongly decrease subjective well-being (or "happiness"). In the present paper, we use panel quantile regression techniques in order to analyze to what extent the negative impact of unemployment varies along the subjective well-being distribution. In our...