A0874
Title: Dynamic approaches to ranking happiness: Integrating benefit of the doubt weighting and functional data analysis
Authors: Annalina Sarra - University of Chieti-Pescara (Italy) [presenting]
Eugenia Nissi - University G d Annunzio Chieti Pescara (Italy)
Adelia Evangelista - University of Chieti-Pescara (Italy)
Tonio Di Battista - G. d'Annunzio University of Chieti-Pescara, Italy (Italy)
Abstract: In recent years, the pursuit of happiness has become a key indicator of societal well-being, prompting many countries to measure their Happiness Index. Traditional rankings use static data, which may not fully capture the multifaceted nature of happiness over time. A novel approach is introduced, combining benefit of the doubt (BoD), weighting with functional data analysis (FDA) to create a comprehensive Happiness Index ranking. BoD, used in composite indicators (CIs), flexibly derives weights from the data, allowing for the aggregation of quantitative sub-indicators without precise weight information. After establishing a CI of happiness, the FDA is used to examine how happiness scores evolve over time. Two functional measures are specifically utilized: the modified hypograph index (MHI) and the weighted integrated first derivative (DW). The MHI assesses the proportion of time during which one country's performance surpasses others, while the DW measures the duration and direction of trends in a country's performance trajectory, capturing early signs of improvement or decline. This approach provides an informative comparison of countries, highlighting not only their current standings but also their trends and trajectories over time. The methodology was used on a combined dataset from various sources to estimate worldwide happiness from 2005 to 2023.
