Health indicators as determinants of happiness levels in countries: Ordered logistic regression analysis - Dilek Veysikarani Geyik (Journal of Life Economics, 2026)
Purpose: This study examines the association between selected health indicators and countries’ happiness levels. It specifically investigates whether health-system resources and health outcomes are associated with the likelihood of countries being classified into different levels of happiness. Method: Cross-sectional data for 127 countries in 2023 were used. Countries’ happiness scores were classified into low, medium, and high categories based on the 33rd and 66th percentiles. Given the ordinal structure of the dependent variable, an ordinal logistic regression model was estimated. Current health expenditure, life expectancy at birth, infant mortality rate, and out-of-pocket health expenditure were included as explanatory variables. The proportional odds assumption was assessed using the Brant test. Findings: Current health expenditure is positively and statistically significantly associated with higher happiness categories at the 1% significance level. Life expectancy at birth is positively associated with higher happiness, while infant mortality is negatively associated with happiness, with both effects statistically significant at the 10% level. Out-of-pocket health expenditure has no statistically significant association with happiness. The model achieves an overall classification accuracy of 72.44%. Conclusion/Contribution: The findings indicate that health-system resources and population health outcomes are closely associated with national well-being. The study contributes to the literature by modelling happiness as an ordered categorical outcome rather than a continuous variable, thereby providing a differentiated assessment of health-related determinants across distinct happiness levels.