Article Details

Title Subjective Financial Well-Being An Explorative Analysis by Algorithmic Modeling Techniques
Authors Christiaans, Thomas, Luebke, Karsten and Richenhagen, Julia
Year 2018
Volume Archives of Data Science, Series A 4(1) / 2018
Abstract Taking non-rational behavior and incomplete information into account, actual income distributions and financial well-being probably deviate from their perceptions. Based on a questionnaire sample of more than 45,000 Germans we investigate which socio-economic variables and combinations of these may help to model subjective financial well-being. Additionally to age, gender, and regional information, (perceived) household income and local and country-wide rankings of income distribution are used as possible modeling variables. The link is investigated by means of ordinary least squares regression as well as tree based methods. It turns out that on our sample, additionally to subjective income class and reported actual income, age, region and, though to a lower extend, gender help to model subjective financial well-being.