Scaling up the process of variable valuation based on subjective wellbeing: A methodological research

Abstract

Impact assessment is the first step to understand the positive and negative effects created by an activity or product. Social impact is not often measured quantitatively, and this prevents social impact data to be presented side by side with environmental and financial impact data. Methodologies have been developed to measure social impact based on the effects that selected variables have on subjective wellbeing, and present these as a monetary value. Existing methodologies however rely on very specific primary data collection methods and this requires a great amount of time and financial resources. The goal of this thesis is to adapt these published methodologies to solely require secondary data. This builds on existing theories and can be directly applied in real life situations where for example a company wants to measure its social impacts. To do this, an overview of the existing published methodologies was carried out and the “Three Stage Wellbeing Valuation” approach (3S-WV) stood out as being the most complete and well explained methodology. This led to an in-depth understanding of this paper that would then allow for its adaptation, and an evaluation of its strengths and limitations. The European Social Survey database (ESS) was chosen as main source of secondary data for this adaptation as it has a strong research background, is carried out frequently with thousands of European citizens and is publicly available. The 3S-WV has three stages, the income model (where the relationship between income and wellbeing is determined), the non-market good model (where the relationship between the variable in question and wellbeing is determined) and the monetary equivalent value (where the previous two stages are combined to reach a monetary value). For the purpose of validation, the variable unemployment was used to test the adaptation of the methodology and when comparing the value obtained using secondary data to the one obtained in the published paper where primary data was used, the difference was minimal. This leads to the conclusion that this methodology is worth pursuing in further research that would start by carrying out the valuation of more variables and carrying out a statistical analysis of these results.