Latent variable models represent a useful tool in different fields of research in which the constructs of interest are not directly observable. In such models, problems related to the integration of the likelihood function can arise since analytical solutions do not exist. Numerical...

We argue that the relationship between individual satisfaction with life (SWL) and SWL inequality is more complex than described by leading earlier research such as Goff, Helliwell, and Mayraz (Economic Inquiry, 2018). Using inequality indices appropriate for ordinal data, our analysis using the...

We review two complementary mixture-based clustering approaches for modeling unobserved heterogeneity in an insurance portfolio: the generalized linear mixed cluster-weighted model (CWM) and mixture-based clustering for an ordered stereotype model (OSM). The latter is for modeling of ordinal...

To compare distributions of ordinal data such as individuals' responses on Likert-type scale variables summarizing subjective well-being, we should not apply the toolbox of methods developed for cardinal variables such as income. Instead we should use an analogous toolbox which takes account of...

How to undertake distributional comparisons when personal well-being is measured using income is well-established. But what if personal well-being is measured using subjective well-being indicators such as life satisfaction or self-assessed health status? Has average well-being increased or...

Non-intersection of appropriately-defined Generalized Lorenz (GL) curves is equivalent to a unanimous ranking of distributions of ordinal data by all Cowell and Flachaire (Economica 2017) indices of inequality and by a new index based on GL curve areas. Comparisons of life satisfaction...