Canonical correlation analysis (CCA) is a robust multivariate statistical method primarily used to examine comprehensive correlations between two multivariate datasets. With broad applications spanning economics

psychology

and medicine

this technique helps identify hidden latent variables and theoretical dimensions

revealing complex multidimensional relationships between variables. This study investigates the correlation between macroeconomic indicators and social welfare systems using data from over 50 countries

comprising two variable groups: economic indicators and social welfare metrics. Through CCA

the study demonstrates how two representative variables effectively explain their correlation levels

while discussing its academic value and policy implications. The findings provide new empirical evidence and analytical frameworks for understanding the synergy and inherent tensions between economic and social development.