Longitudinal Analysis of World Happiness Scores (2015–2019)

Abstract

The World Happiness Report provides annual data on self-reported life satisfaction and associated socio-economic factors for countries worldwide. In this study, a statistical model is used to explain and predict national happiness scores from 2015 to 2019 using six key factors (GDP, social support, healthy life expectancy, freedom, generosity, and corruption perceptions). The linear mixed-effects model is employed to account for repeated measurements for each country over time, including country-specific random intercepts. The mixed model captures both the differences between countries and the changes in happiness over time. Results show that GDP per capita, freedom to make life choices, and healthy life expectancy are significant positive predictors of happiness, while factors like generosity have a more minor and statistically insignificant effect when other variables are controlled. Social support did not exhibit a significant independent effect in the multivariate context. There is substantial unexplained variance between countries, validating the inclusion of country-level random effects. The model achieves high predictive accuracy (conditional R² ≈ 0.93), and diagnostic checks indicate assumptions are satisfied. These findings underscore the importance of economic and personal freedom factors in national happiness and highlight that country-specific characteristics play a significant role.