Abstract
This study examines the relationship between Baccalaureate pass rates, unemployment rates, and average income levels across Romanian counties in 2023. Using secondary statistical data from official national sources, we applied a range of quantitative methods, including bivariate correlations, multiple linear regression, and spatial econometric modeling, to explore these socio-economic interdependencies. Findings indicate a moderate but statistically non-significant negative correlation between pass rates and unemployment, suggesting that higher educational achievement may be associated with lower unemployment, though this relationship lacks robust statistical support. In contrast, average income levels emerged as a significant negative predictor of unemployment in the multiple regression model. Spatial regression analysis further revealed substantial spatial autocorrelation in unemployment rates, indicating that neighboring counties tend to exhibit similar labor market dynamics. These results highlight the importance of integrating both socio-economic and spatial dimensions into policy frameworks aimed at reducing regional disparities in employment and fostering equitable development.