A Regression-Based Predictive Analysis of National Happiness Index: Evidence from the World Happiness Report (2006–2023)

Abstract

This study investigates the relationship between economic development and national happiness using panel data from the World Happiness Report covering the period from 2006 to 2023. Previous studies have generally suggested that income is positively associated with subjective well-being, but questions remain regarding the stability of this relationship across countries and over time. To address these issues, this study employs a regression-based empirical framework that combines correlation analysis, baseline linear regression, income-group comparison using a Welch two-sample t-test, and a time-interaction regression model. In addition, a prediction framework is developed to estimate happiness outcomes under different economic conditions. The empirical results reveal a strong positive association between log GDP per capita and national happiness levels. Significant differences in happiness are also observed between high-income and low-income countries. However, the interaction analysis suggests that the economic effect on happiness remains relatively stable over the sample period. The prediction model further demonstrates that economic indicators possess substantial explanatory and predictive power for national happiness. Overall, the findings indicate that economic development plays an important but incomplete role in shaping subjective well-being across countries and that non-economic factors may also contribute to differences in happiness levels.